Overview

Dataset statistics

Number of variables59
Number of observations86
Missing cells1920
Missing cells (%)37.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.8 KiB
Average record size in memory473.5 B

Variable types

Numeric12
Categorical38
Unsupported9

Alerts

airdate has constant value "2020-12-07" Constant
url has a high cardinality: 86 distinct values High cardinality
name has a high cardinality: 66 distinct values High cardinality
_links.self.href has a high cardinality: 86 distinct values High cardinality
_embedded.show.url has a high cardinality: 59 distinct values High cardinality
_embedded.show.name has a high cardinality: 59 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 55 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 55 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 55 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 59 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 59 distinct values High cardinality
id is highly correlated with rating.average and 3 other fieldsHigh correlation
season is highly correlated with number and 7 other fieldsHigh correlation
number is highly correlated with season and 4 other fieldsHigh correlation
runtime is highly correlated with rating.average and 4 other fieldsHigh correlation
rating.average is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 12 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 11 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 7 other fieldsHigh correlation
_embedded.show.updated is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with season and 6 other fieldsHigh correlation
id is highly correlated with rating.average and 1 other fieldsHigh correlation
season is highly correlated with number and 5 other fieldsHigh correlation
number is highly correlated with season and 3 other fieldsHigh correlation
runtime is highly correlated with rating.average and 4 other fieldsHigh correlation
rating.average is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 12 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with season and 9 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with season and 6 other fieldsHigh correlation
id is highly correlated with rating.average and 1 other fieldsHigh correlation
season is highly correlated with rating.average and 3 other fieldsHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 4 other fieldsHigh correlation
rating.average is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 12 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with runtime and 6 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with season and 5 other fieldsHigh correlation
id is highly correlated with url and 32 other fieldsHigh correlation
url is highly correlated with id and 46 other fieldsHigh correlation
name is highly correlated with id and 41 other fieldsHigh correlation
season is highly correlated with url and 24 other fieldsHigh correlation
number is highly correlated with url and 38 other fieldsHigh correlation
type is highly correlated with url and 12 other fieldsHigh correlation
airtime is highly correlated with url and 39 other fieldsHigh correlation
airstamp is highly correlated with url and 44 other fieldsHigh correlation
runtime is highly correlated with url and 41 other fieldsHigh correlation
summary is highly correlated with id and 37 other fieldsHigh correlation
_links.self.href is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.type is highly correlated with url and 41 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.status is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with url and 41 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with url and 43 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with url and 40 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with url and 21 other fieldsHigh correlation
_embedded.show.weight is highly correlated with url and 39 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with url and 22 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 36 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 32 other fieldsHigh correlation
image.medium is highly correlated with id and 37 other fieldsHigh correlation
image.original is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 36 other fieldsHigh correlation
number has 1 (1.2%) missing values Missing
runtime has 4 (4.7%) missing values Missing
image has 86 (100.0%) missing values Missing
summary has 64 (74.4%) missing values Missing
rating.average has 84 (97.7%) missing values Missing
_embedded.show.language has 2 (2.3%) missing values Missing
_embedded.show.runtime has 22 (25.6%) missing values Missing
_embedded.show.averageRuntime has 1 (1.2%) missing values Missing
_embedded.show.ended has 41 (47.7%) missing values Missing
_embedded.show.officialSite has 8 (9.3%) missing values Missing
_embedded.show.rating.average has 83 (96.5%) missing values Missing
_embedded.show.network has 86 (100.0%) missing values Missing
_embedded.show.webChannel.id has 1 (1.2%) missing values Missing
_embedded.show.webChannel.name has 1 (1.2%) missing values Missing
_embedded.show.webChannel.country.name has 53 (61.6%) missing values Missing
_embedded.show.webChannel.country.code has 53 (61.6%) missing values Missing
_embedded.show.webChannel.country.timezone has 53 (61.6%) missing values Missing
_embedded.show.webChannel.officialSite has 48 (55.8%) missing values Missing
_embedded.show.dvdCountry has 86 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 83 (96.5%) missing values Missing
_embedded.show.externals.thetvdb has 18 (20.9%) missing values Missing
_embedded.show.externals.imdb has 44 (51.2%) missing values Missing
_embedded.show.image.medium has 10 (11.6%) missing values Missing
_embedded.show.image.original has 10 (11.6%) missing values Missing
_embedded.show.summary has 15 (17.4%) missing values Missing
_embedded.show._links.nextepisode.href has 79 (91.9%) missing values Missing
image.medium has 70 (81.4%) missing values Missing
image.original has 70 (81.4%) missing values Missing
_embedded.show.network.id has 80 (93.0%) missing values Missing
_embedded.show.network.name has 80 (93.0%) missing values Missing
_embedded.show.network.country.name has 80 (93.0%) missing values Missing
_embedded.show.network.country.code has 80 (93.0%) missing values Missing
_embedded.show.network.country.timezone has 80 (93.0%) missing values Missing
_embedded.show.network.officialSite has 86 (100.0%) missing values Missing
_embedded.show.webChannel.country has 86 (100.0%) missing values Missing
_embedded.show.image has 86 (100.0%) missing values Missing
_embedded.show.webChannel has 86 (100.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.externals.tvrage is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show.network.country.name is uniformly distributed Uniform
_embedded.show.network.country.code is uniformly distributed Uniform
_embedded.show.network.country.timezone is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:38:43.373824
Analysis finished2022-09-06 02:39:04.875384
Duration21.5 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2022961.43
Minimum1945591
Maximum2374501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:04.947842image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1945591
5-th percentile1969487.25
Q11978014
median1984801.5
Q32004915.25
95-th percentile2211134.75
Maximum2374501
Range428910
Interquartile range (IQR)26901.25

Descriptive statistics

Standard deviation93008.24145
Coefficient of variation (CV)0.04597628015
Kurtosis5.660270156
Mean2022961.43
Median Absolute Deviation (MAD)11547
Skewness2.477726347
Sum173974683
Variance8650532978
MonotonicityNot monotonic
2022-09-05T21:39:05.064182image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19792451
 
1.2%
19963491
 
1.2%
20433011
 
1.2%
20249101
 
1.2%
19963551
 
1.2%
19963541
 
1.2%
19963531
 
1.2%
19963521
 
1.2%
19963511
 
1.2%
19963501
 
1.2%
Other values (76)76
88.4%
ValueCountFrequency (%)
19455911
1.2%
19600311
1.2%
19656461
1.2%
19679281
1.2%
19690611
1.2%
19707661
1.2%
19712021
1.2%
19712031
1.2%
19712041
1.2%
19712051
1.2%
ValueCountFrequency (%)
23745011
1.2%
23682961
1.2%
23369071
1.2%
23180991
1.2%
22111351
1.2%
22111341
1.2%
21954101
1.2%
21761241
1.2%
21698511
1.2%
21525841
1.2%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size816.0 B
https://www.tvmaze.com/episodes/1979245/volk-1x01-seria-01
 
1
https://www.tvmaze.com/episodes/1996349/fixer-1x02-episode-2
 
1
https://www.tvmaze.com/episodes/2043301/the-college-tour-1x02-florida-tech
 
1
https://www.tvmaze.com/episodes/2024910/el-anesa-farah-2x17-episode-17
 
1
https://www.tvmaze.com/episodes/1996355/fixer-1x08-episode-8
 
1
Other values (81)
81 

Length

Max length158
Median length100
Mean length79.40697674
Min length58

Characters and Unicode

Total characters6829
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1979245/volk-1x01-seria-01
2nd rowhttps://www.tvmaze.com/episodes/1981560/volk-1x02-seria-02
3rd rowhttps://www.tvmaze.com/episodes/1986869/kotiki-1x06-seria-6
4th rowhttps://www.tvmaze.com/episodes/2140386/going-seventeen-2020-12-07-dont-lie-ii-2
5th rowhttps://www.tvmaze.com/episodes/1945591/my-little-invisible-being-1x11-episode-11

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1979245/volk-1x01-seria-011
 
1.2%
https://www.tvmaze.com/episodes/1996349/fixer-1x02-episode-21
 
1.2%
https://www.tvmaze.com/episodes/2043301/the-college-tour-1x02-florida-tech1
 
1.2%
https://www.tvmaze.com/episodes/2024910/el-anesa-farah-2x17-episode-171
 
1.2%
https://www.tvmaze.com/episodes/1996355/fixer-1x08-episode-81
 
1.2%
https://www.tvmaze.com/episodes/1996354/fixer-1x07-episode-71
 
1.2%
https://www.tvmaze.com/episodes/1996353/fixer-1x06-episode-61
 
1.2%
https://www.tvmaze.com/episodes/1996352/fixer-1x05-episode-51
 
1.2%
https://www.tvmaze.com/episodes/1996351/fixer-1x04-episode-41
 
1.2%
https://www.tvmaze.com/episodes/1996350/fixer-1x03-episode-31
 
1.2%
Other values (76)76
88.4%

Length

2022-09-05T21:39:05.199993image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1979245/volk-1x01-seria-011
 
1.2%
https://www.tvmaze.com/episodes/1982914/alex-og-aune-1x05-pa-gjengrodde-stier1
 
1.2%
https://www.tvmaze.com/episodes/2140386/going-seventeen-2020-12-07-dont-lie-ii-21
 
1.2%
https://www.tvmaze.com/episodes/1945591/my-little-invisible-being-1x11-episode-111
 
1.2%
https://www.tvmaze.com/episodes/2065440/the-wonderland-of-ten-thousands-4x27-episode-27-1551
 
1.2%
https://www.tvmaze.com/episodes/2080223/supreme-god-emperor-1x61-episode-611
 
1.2%
https://www.tvmaze.com/episodes/1977315/stjernestov-1x07-episode-71
 
1.2%
https://www.tvmaze.com/episodes/2003092/slepaa-10x96-kto-v-dome-zivet1
 
1.2%
https://www.tvmaze.com/episodes/1981501/esenepozner-s02-special-zakladka-39-v-poiskah-grazdanskoj-oborony-konstantinopola-i-operatora-antonioni1
 
1.2%
https://www.tvmaze.com/episodes/1978779/kuad-wicha-by-brands-summer-camp-1x05-episode-51
 
1.2%
Other values (76)76
88.4%

Most occurring characters

ValueCountFrequency (%)
e587
 
8.6%
-521
 
7.6%
/430
 
6.3%
s428
 
6.3%
t406
 
5.9%
o363
 
5.3%
w285
 
4.2%
i281
 
4.1%
a269
 
3.9%
p260
 
3.8%
Other values (30)2999
43.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4592
67.2%
Decimal Number1028
 
15.1%
Other Punctuation688
 
10.1%
Dash Punctuation521
 
7.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e587
12.8%
s428
 
9.3%
t406
 
8.8%
o363
 
7.9%
w285
 
6.2%
i281
 
6.1%
a269
 
5.9%
p260
 
5.7%
m225
 
4.9%
d197
 
4.3%
Other values (16)1291
28.1%
Decimal Number
ValueCountFrequency (%)
1233
22.7%
0149
14.5%
2140
13.6%
9119
11.6%
774
 
7.2%
667
 
6.5%
365
 
6.3%
464
 
6.2%
562
 
6.0%
855
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/430
62.5%
.172
 
25.0%
:86
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-521
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4592
67.2%
Common2237
32.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e587
12.8%
s428
 
9.3%
t406
 
8.8%
o363
 
7.9%
w285
 
6.2%
i281
 
6.1%
a269
 
5.9%
p260
 
5.7%
m225
 
4.9%
d197
 
4.3%
Other values (16)1291
28.1%
Common
ValueCountFrequency (%)
-521
23.3%
/430
19.2%
1233
10.4%
.172
 
7.7%
0149
 
6.7%
2140
 
6.3%
9119
 
5.3%
:86
 
3.8%
774
 
3.3%
667
 
3.0%
Other values (4)246
11.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6829
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e587
 
8.6%
-521
 
7.6%
/430
 
6.3%
s428
 
6.3%
t406
 
5.9%
o363
 
5.3%
w285
 
4.2%
i281
 
4.1%
a269
 
3.9%
p260
 
3.8%
Other values (30)2999
43.9%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct66
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size816.0 B
Episode 2
 
4
Episode 1
 
4
Episode 7
 
3
Episode 4
 
3
Episode 20
 
3
Other values (61)
69 

Length

Max length96
Median length82
Mean length18.76744186
Min length7

Characters and Unicode

Total characters1614
Distinct characters113
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)64.0%

Sample

1st rowСерия 01
2nd rowСерия 02
3rd rowСерия 6
4th rowDon't Lie Ⅱ #2
5th rowEpisode 11

Common Values

ValueCountFrequency (%)
Episode 24
 
4.7%
Episode 14
 
4.7%
Episode 73
 
3.5%
Episode 43
 
3.5%
Episode 203
 
3.5%
Episode 33
 
3.5%
Episode 53
 
3.5%
Episode 242
 
2.3%
Episode 232
 
2.3%
Episode 192
 
2.3%
Other values (56)57
66.3%

Length

2022-09-05T21:39:05.317521image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode43
 
14.7%
17
 
2.4%
27
 
2.4%
6
 
2.1%
solar6
 
2.1%
the6
 
2.1%
75
 
1.7%
car4
 
1.4%
серия4
 
1.4%
a3
 
1.0%
Other values (174)201
68.8%

Most occurring characters

ValueCountFrequency (%)
206
 
12.8%
e123
 
7.6%
i96
 
5.9%
o91
 
5.6%
s73
 
4.5%
a71
 
4.4%
d66
 
4.1%
r53
 
3.3%
n52
 
3.2%
p50
 
3.1%
Other values (103)733
45.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1047
64.9%
Uppercase Letter216
 
13.4%
Space Separator206
 
12.8%
Decimal Number107
 
6.6%
Other Punctuation30
 
1.9%
Dash Punctuation5
 
0.3%
Close Punctuation1
 
0.1%
Open Punctuation1
 
0.1%
Letter Number1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e123
 
11.7%
i96
 
9.2%
o91
 
8.7%
s73
 
7.0%
a71
 
6.8%
d66
 
6.3%
r53
 
5.1%
n52
 
5.0%
p50
 
4.8%
l43
 
4.1%
Other values (41)329
31.4%
Uppercase Letter
ValueCountFrequency (%)
E46
21.3%
S19
 
8.8%
C15
 
6.9%
T10
 
4.6%
A10
 
4.6%
B8
 
3.7%
F8
 
3.7%
W7
 
3.2%
G7
 
3.2%
R7
 
3.2%
Other values (30)79
36.6%
Decimal Number
ValueCountFrequency (%)
226
24.3%
121
19.6%
011
10.3%
310
 
9.3%
710
 
9.3%
47
 
6.5%
97
 
6.5%
67
 
6.5%
55
 
4.7%
83
 
2.8%
Other Punctuation
ValueCountFrequency (%)
,11
36.7%
'8
26.7%
#5
16.7%
:3
 
10.0%
?1
 
3.3%
.1
 
3.3%
&1
 
3.3%
Space Separator
ValueCountFrequency (%)
206
100.0%
Dash Punctuation
ValueCountFrequency (%)
-5
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1068
66.2%
Common350
 
21.7%
Cyrillic196
 
12.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e123
 
11.5%
i96
 
9.0%
o91
 
8.5%
s73
 
6.8%
a71
 
6.6%
d66
 
6.2%
r53
 
5.0%
n52
 
4.9%
p50
 
4.7%
E46
 
4.3%
Other values (38)347
32.5%
Cyrillic
ValueCountFrequency (%)
о20
 
10.2%
и18
 
9.2%
а14
 
7.1%
н10
 
5.1%
р10
 
5.1%
е8
 
4.1%
я8
 
4.1%
л7
 
3.6%
к7
 
3.6%
т6
 
3.1%
Other values (34)88
44.9%
Common
ValueCountFrequency (%)
206
58.9%
226
 
7.4%
121
 
6.0%
,11
 
3.1%
011
 
3.1%
310
 
2.9%
710
 
2.9%
'8
 
2.3%
47
 
2.0%
97
 
2.0%
Other values (11)33
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1416
87.7%
Cyrillic196
 
12.1%
None1
 
0.1%
Number Forms1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
206
 
14.5%
e123
 
8.7%
i96
 
6.8%
o91
 
6.4%
s73
 
5.2%
a71
 
5.0%
d66
 
4.7%
r53
 
3.7%
n52
 
3.7%
p50
 
3.5%
Other values (57)535
37.8%
Cyrillic
ValueCountFrequency (%)
о20
 
10.2%
и18
 
9.2%
а14
 
7.1%
н10
 
5.1%
р10
 
5.1%
е8
 
4.1%
я8
 
4.1%
л7
 
3.6%
к7
 
3.6%
т6
 
3.1%
Other values (34)88
44.9%
None
ValueCountFrequency (%)
å1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct13
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167.4651163
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:05.410674image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)3

Descriptive statistics

Standard deviation554.7100503
Coefficient of variation (CV)3.312391635
Kurtosis7.892466372
Mean167.4651163
Median Absolute Deviation (MAD)0
Skewness3.115749125
Sum14402
Variance307703.2399
MonotonicityNot monotonic
2022-09-05T21:39:05.504227image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
155
64.0%
20207
 
8.1%
47
 
8.1%
26
 
7.0%
182
 
2.3%
32
 
2.3%
101
 
1.2%
301
 
1.2%
91
 
1.2%
121
 
1.2%
Other values (3)3
 
3.5%
ValueCountFrequency (%)
155
64.0%
26
 
7.0%
32
 
2.3%
47
 
8.1%
61
 
1.2%
91
 
1.2%
101
 
1.2%
121
 
1.2%
182
 
2.3%
271
 
1.2%
ValueCountFrequency (%)
20207
8.1%
311
 
1.2%
301
 
1.2%
271
 
1.2%
182
 
2.3%
121
 
1.2%
101
 
1.2%
91
 
1.2%
61
 
1.2%
47
8.1%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct38
Distinct (%)44.7%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean30.72941176
Minimum1
Maximum334
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:05.602477image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median9
Q324
95-th percentile136
Maximum334
Range333
Interquartile range (IQR)21

Descriptive statistics

Standard deviation62.59286211
Coefficient of variation (CV)2.036904012
Kurtosis13.22455748
Mean30.72941176
Median Absolute Deviation (MAD)8
Skewness3.615119898
Sum2612
Variance3917.866387
MonotonicityNot monotonic
2022-09-05T21:39:05.719456image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
19
 
10.5%
28
 
9.3%
56
 
7.0%
36
 
7.0%
45
 
5.8%
494
 
4.7%
203
 
3.5%
63
 
3.5%
113
 
3.5%
73
 
3.5%
Other values (28)35
40.7%
ValueCountFrequency (%)
19
10.5%
28
9.3%
36
7.0%
45
5.8%
56
7.0%
63
 
3.5%
73
 
3.5%
81
 
1.2%
93
 
3.5%
101
 
1.2%
ValueCountFrequency (%)
3341
1.2%
2921
1.2%
2911
1.2%
2331
1.2%
1461
1.2%
961
1.2%
791
1.2%
611
1.2%
601
1.2%
571
1.2%

type
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size816.0 B
regular
85 
insignificant_special
 
1

Length

Max length21
Median length7
Mean length7.162790698
Min length7

Characters and Unicode

Total characters616
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular85
98.8%
insignificant_special1
 
1.2%

Length

2022-09-05T21:39:05.838536image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:05.934617image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular85
98.8%
insignificant_special1
 
1.2%

Most occurring characters

ValueCountFrequency (%)
r170
27.6%
a87
14.1%
e86
14.0%
g86
14.0%
l86
14.0%
u85
13.8%
i5
 
0.8%
n3
 
0.5%
s2
 
0.3%
c2
 
0.3%
Other values (4)4
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter615
99.8%
Connector Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r170
27.6%
a87
14.1%
e86
14.0%
g86
14.0%
l86
14.0%
u85
13.8%
i5
 
0.8%
n3
 
0.5%
s2
 
0.3%
c2
 
0.3%
Other values (3)3
 
0.5%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin615
99.8%
Common1
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
r170
27.6%
a87
14.1%
e86
14.0%
g86
14.0%
l86
14.0%
u85
13.8%
i5
 
0.8%
n3
 
0.5%
s2
 
0.3%
c2
 
0.3%
Other values (3)3
 
0.5%
Common
ValueCountFrequency (%)
_1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII616
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r170
27.6%
a87
14.1%
e86
14.0%
g86
14.0%
l86
14.0%
u85
13.8%
i5
 
0.8%
n3
 
0.5%
s2
 
0.3%
c2
 
0.3%
Other values (4)4
 
0.6%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size816.0 B
2020-12-07
86 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters860
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-07
2nd row2020-12-07
3rd row2020-12-07
4th row2020-12-07
5th row2020-12-07

Common Values

ValueCountFrequency (%)
2020-12-0786
100.0%

Length

2022-09-05T21:39:06.010981image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:06.108053image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-0786
100.0%

Most occurring characters

ValueCountFrequency (%)
2258
30.0%
0258
30.0%
-172
20.0%
186
 
10.0%
786
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number688
80.0%
Dash Punctuation172
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2258
37.5%
0258
37.5%
186
 
12.5%
786
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common860
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2258
30.0%
0258
30.0%
-172
20.0%
186
 
10.0%
786
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2258
30.0%
0258
30.0%
-172
20.0%
186
 
10.0%
786
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size816.0 B
62 
20:00
15 
21:00
 
3
12:00
 
1
06:00
 
1
Other values (4)
 
4

Length

Max length5
Median length0
Mean length1.395348837
Min length0

Characters and Unicode

Total characters120
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)7.0%

Sample

1st row
2nd row
3rd row
4th row
5th row12:00

Common Values

ValueCountFrequency (%)
62
72.1%
20:0015
 
17.4%
21:003
 
3.5%
12:001
 
1.2%
06:001
 
1.2%
17:351
 
1.2%
00:001
 
1.2%
19:001
 
1.2%
20:151
 
1.2%

Length

2022-09-05T21:39:06.198235image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:06.330434image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
20:0015
62.5%
21:003
 
12.5%
12:001
 
4.2%
06:001
 
4.2%
17:351
 
4.2%
00:001
 
4.2%
19:001
 
4.2%
20:151
 
4.2%

Most occurring characters

ValueCountFrequency (%)
063
52.5%
:24
 
20.0%
220
 
16.7%
17
 
5.8%
52
 
1.7%
61
 
0.8%
71
 
0.8%
31
 
0.8%
91
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number96
80.0%
Other Punctuation24
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
063
65.6%
220
 
20.8%
17
 
7.3%
52
 
2.1%
61
 
1.0%
71
 
1.0%
31
 
1.0%
91
 
1.0%
Other Punctuation
ValueCountFrequency (%)
:24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common120
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
063
52.5%
:24
 
20.0%
220
 
16.7%
17
 
5.8%
52
 
1.7%
61
 
0.8%
71
 
0.8%
31
 
0.8%
91
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
063
52.5%
:24
 
20.0%
220
 
16.7%
17
 
5.8%
52
 
1.7%
61
 
0.8%
71
 
0.8%
31
 
0.8%
91
 
0.8%

airstamp
Categorical

HIGH CORRELATION

Distinct17
Distinct (%)19.8%
Missing0
Missing (%)0.0%
Memory size816.0 B
2020-12-07T12:00:00+00:00
58 
2020-12-07T17:00:00+00:00
2020-12-07T00:00:00+00:00
 
3
2020-12-07T04:00:00+00:00
 
3
2020-12-07T21:00:00+00:00
 
2
Other values (12)
14 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2150
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)11.6%

Sample

1st row2020-12-07T00:00:00+00:00
2nd row2020-12-07T00:00:00+00:00
3rd row2020-12-07T00:00:00+00:00
4th row2020-12-07T03:00:00+00:00
5th row2020-12-07T04:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-07T12:00:00+00:0058
67.4%
2020-12-07T17:00:00+00:006
 
7.0%
2020-12-07T00:00:00+00:003
 
3.5%
2020-12-07T04:00:00+00:003
 
3.5%
2020-12-07T21:00:00+00:002
 
2.3%
2020-12-07T11:00:00+00:002
 
2.3%
2020-12-07T19:00:00+00:002
 
2.3%
2020-12-07T16:00:00+00:001
 
1.2%
2020-12-08T01:00:00+00:001
 
1.2%
2020-12-07T19:15:00+00:001
 
1.2%
Other values (7)7
 
8.1%

Length

2022-09-05T21:39:06.419825image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-07t12:00:00+00:0058
67.4%
2020-12-07t17:00:00+00:006
 
7.0%
2020-12-07t00:00:00+00:003
 
3.5%
2020-12-07t04:00:00+00:003
 
3.5%
2020-12-07t21:00:00+00:002
 
2.3%
2020-12-07t11:00:00+00:002
 
2.3%
2020-12-07t19:00:00+00:002
 
2.3%
2020-12-07t03:00:00+00:001
 
1.2%
2020-12-07t05:00:00+00:001
 
1.2%
2020-12-07t05:35:00+00:001
 
1.2%
Other values (7)7
 
8.1%

Most occurring characters

ValueCountFrequency (%)
0957
44.5%
2319
 
14.8%
:258
 
12.0%
-172
 
8.0%
1164
 
7.6%
790
 
4.2%
T86
 
4.0%
+86
 
4.0%
55
 
0.2%
44
 
0.2%
Other values (4)9
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1548
72.0%
Other Punctuation258
 
12.0%
Dash Punctuation172
 
8.0%
Uppercase Letter86
 
4.0%
Math Symbol86
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0957
61.8%
2319
 
20.6%
1164
 
10.6%
790
 
5.8%
55
 
0.3%
44
 
0.3%
93
 
0.2%
83
 
0.2%
32
 
0.1%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:258
100.0%
Dash Punctuation
ValueCountFrequency (%)
-172
100.0%
Uppercase Letter
ValueCountFrequency (%)
T86
100.0%
Math Symbol
ValueCountFrequency (%)
+86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2064
96.0%
Latin86
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0957
46.4%
2319
 
15.5%
:258
 
12.5%
-172
 
8.3%
1164
 
7.9%
790
 
4.4%
+86
 
4.2%
55
 
0.2%
44
 
0.2%
93
 
0.1%
Other values (3)6
 
0.3%
Latin
ValueCountFrequency (%)
T86
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0957
44.5%
2319
 
14.8%
:258
 
12.0%
-172
 
8.0%
1164
 
7.6%
790
 
4.2%
T86
 
4.0%
+86
 
4.0%
55
 
0.2%
44
 
0.2%
Other values (4)9
 
0.4%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct36
Distinct (%)43.9%
Missing4
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean39.85365854
Minimum2
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:06.516563image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8.1
Q118
median31
Q349.5
95-th percentile118.55
Maximum180
Range178
Interquartile range (IQR)31.5

Descriptive statistics

Standard deviation31.95255818
Coefficient of variation (CV)0.8017471758
Kurtosis4.718956855
Mean39.85365854
Median Absolute Deviation (MAD)15
Skewness1.899582454
Sum3268
Variance1020.965974
MonotonicityNot monotonic
2022-09-05T21:39:06.626439image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
4510
 
11.6%
609
 
10.5%
204
 
4.7%
184
 
4.7%
304
 
4.7%
233
 
3.5%
53
 
3.5%
253
 
3.5%
123
 
3.5%
1203
 
3.5%
Other values (26)36
41.9%
(Missing)4
 
4.7%
ValueCountFrequency (%)
21
 
1.2%
53
3.5%
81
 
1.2%
102
2.3%
111
 
1.2%
123
3.5%
131
 
1.2%
141
 
1.2%
152
2.3%
163
3.5%
ValueCountFrequency (%)
1801
 
1.2%
1301
 
1.2%
1203
 
3.5%
911
 
1.2%
902
 
2.3%
631
 
1.2%
609
10.5%
521
 
1.2%
502
 
2.3%
482
 
2.3%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing86
Missing (%)100.0%
Memory size816.0 B

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct22
Distinct (%)100.0%
Missing64
Missing (%)74.4%
Memory size816.0 B
<p>НТВ 27.12.2021 https://www.ntv.ru/serial/Volk/</p>
 
1
<p>Welcome to LIGHT SPEED! Join Derek Muller of Veritasium to meet the minds (and understand the physics!) behind the world's most advanced solar vehicles. They'll race 2,000 miles across the Australian Outback to test their tech and teamwork, risking life and limb to build a better, more sustainable world.</p>
 
1
<p>Managing director Barry visits the Walsall branch to help with the launch of Project Diamond - a multimillion-pound investment into giving stores a makeover and branching into new product lines like frozen and chilled food.</p>
 
1
<p>From humble beginnings to legendary baseball player and current CEO, A-Rod shares his success story.</p>
 
1
<p>Join Gus Sorola, Gavin Free, Blaine Gibson, and Barbara Dunkelman as they discuss Gus's trash internet, trying not to spoil Mandalorian, Dominick the stupid Christmas Donkey, and more on this week's RT Podcast!</p>
 
1
Other values (17)
17 

Length

Max length409
Median length169.5
Mean length186
Min length53

Characters and Unicode

Total characters4092
Distinct characters71
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row<p>НТВ 27.12.2021 https://www.ntv.ru/serial/Volk/</p>
2nd row<p>Shatter Squad races to a secluded Fort Operating Base. The Mission: Protect Lavernius Tucker and prevent his sword from falling into the clutches of Viper. </p>
3rd row<p>Rachael Ray makes a Korean-style meal in a bowl, loaded with protein, vegetables, sticky rice and an egg on top.</p>
4th row<p>Yevgeny Petrosyan for the first time talks frankly about the birth of his son, his divorce from Еlena Stepanenko, his new wife, modern humor, stand-up, his own critics, sacrifice for the profession, the national question, life and profession. </p>
5th row<p>Dr. Bun has been threatened to manipulate the truth especially since his additional information and evidence support the assumption that Jane did not commit suicide.  But every cloud has a silver lining because this event might spark Tan and Bun's love. </p>

Common Values

ValueCountFrequency (%)
<p>НТВ 27.12.2021 https://www.ntv.ru/serial/Volk/</p>1
 
1.2%
<p>Welcome to LIGHT SPEED! Join Derek Muller of Veritasium to meet the minds (and understand the physics!) behind the world's most advanced solar vehicles. They'll race 2,000 miles across the Australian Outback to test their tech and teamwork, risking life and limb to build a better, more sustainable world.</p>1
 
1.2%
<p>Managing director Barry visits the Walsall branch to help with the launch of Project Diamond - a multimillion-pound investment into giving stores a makeover and branching into new product lines like frozen and chilled food.</p>1
 
1.2%
<p>From humble beginnings to legendary baseball player and current CEO, A-Rod shares his success story.</p>1
 
1.2%
<p>Join Gus Sorola, Gavin Free, Blaine Gibson, and Barbara Dunkelman as they discuss Gus's trash internet, trying not to spoil Mandalorian, Dominick the stupid Christmas Donkey, and more on this week's RT Podcast!</p>1
 
1.2%
<p>Experience extreme academics and unbeatable fun-in-the-sun at Florida Institute of Technology in Melbourne, FL - a short drive from the beach, Kennedy Space Center, and big opportunities. Learn about the university's hands-on degree programs, life on campus, and what it means to be a Florida Tech Panther. We'll take you underwater, into the sky, behind the wheel of a jet dragster and to Mars!<br /> </p>1
 
1.2%
<p>In the finale of our 2,000-mile race across the outback, things are about to take a sharp turn for one of the leading teams. The remaining teams are struggling to survive - but only one can win!</p>1
 
1.2%
<p>On day four, teams scramble to perform repairs as lightning, thunder, and brutal winds batter their encampment.</p>1
 
1.2%
<p>800 kilometers from the finish line, the remaining teams persist through the heat and wind-- some more successfully than others.</p>1
 
1.2%
<p>It's day two and the teams are starting to get tactical, pushing their tech to the limits and then some.</p>1
 
1.2%
Other values (12)12
 
14.0%
(Missing)64
74.4%

Length

2022-09-05T21:39:06.732651image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the40
 
6.3%
and25
 
3.9%
of19
 
3.0%
a18
 
2.8%
to17
 
2.7%
8
 
1.3%
p8
 
1.3%
his7
 
1.1%
as6
 
0.9%
their5
 
0.8%
Other values (400)486
76.1%

Most occurring characters

ValueCountFrequency (%)
610
14.9%
e349
 
8.5%
a276
 
6.7%
t262
 
6.4%
n239
 
5.8%
s222
 
5.4%
i219
 
5.4%
r215
 
5.3%
o210
 
5.1%
h134
 
3.3%
Other values (61)1356
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3044
74.4%
Space Separator619
 
15.1%
Uppercase Letter143
 
3.5%
Other Punctuation133
 
3.3%
Math Symbol108
 
2.6%
Decimal Number23
 
0.6%
Dash Punctuation20
 
0.5%
Close Punctuation1
 
< 0.1%
Open Punctuation1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S13
 
9.1%
M12
 
8.4%
T12
 
8.4%
D11
 
7.7%
B10
 
7.0%
F9
 
6.3%
C7
 
4.9%
I6
 
4.2%
R6
 
4.2%
A6
 
4.2%
Other values (17)51
35.7%
Lowercase Letter
ValueCountFrequency (%)
e349
11.5%
a276
 
9.1%
t262
 
8.6%
n239
 
7.9%
s222
 
7.3%
i219
 
7.2%
r215
 
7.1%
o210
 
6.9%
h134
 
4.4%
l127
 
4.2%
Other values (16)791
26.0%
Other Punctuation
ValueCountFrequency (%)
,43
32.3%
.36
27.1%
/34
25.6%
'11
 
8.3%
!7
 
5.3%
:2
 
1.5%
Decimal Number
ValueCountFrequency (%)
010
43.5%
27
30.4%
14
 
17.4%
81
 
4.3%
71
 
4.3%
Space Separator
ValueCountFrequency (%)
610
98.5%
 9
 
1.5%
Math Symbol
ValueCountFrequency (%)
<54
50.0%
>54
50.0%
Dash Punctuation
ValueCountFrequency (%)
-20
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3183
77.8%
Common905
 
22.1%
Cyrillic4
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e349
 
11.0%
a276
 
8.7%
t262
 
8.2%
n239
 
7.5%
s222
 
7.0%
i219
 
6.9%
r215
 
6.8%
o210
 
6.6%
h134
 
4.2%
l127
 
4.0%
Other values (39)930
29.2%
Common
ValueCountFrequency (%)
610
67.4%
<54
 
6.0%
>54
 
6.0%
,43
 
4.8%
.36
 
4.0%
/34
 
3.8%
-20
 
2.2%
'11
 
1.2%
010
 
1.1%
 9
 
1.0%
Other values (8)24
 
2.7%
Cyrillic
ValueCountFrequency (%)
В1
25.0%
Т1
25.0%
Н1
25.0%
Е1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4079
99.7%
None9
 
0.2%
Cyrillic4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
610
15.0%
e349
 
8.6%
a276
 
6.8%
t262
 
6.4%
n239
 
5.9%
s222
 
5.4%
i219
 
5.4%
r215
 
5.3%
o210
 
5.1%
h134
 
3.3%
Other values (56)1343
32.9%
None
ValueCountFrequency (%)
 9
100.0%
Cyrillic
ValueCountFrequency (%)
В1
25.0%
Т1
25.0%
Н1
25.0%
Е1
25.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing84
Missing (%)97.7%
Memory size816.0 B
10.0
6.0

Length

Max length4
Median length3.5
Mean length3.5
Min length3

Characters and Unicode

Total characters7
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row10.0
2nd row6.0

Common Values

ValueCountFrequency (%)
10.01
 
1.2%
6.01
 
1.2%
(Missing)84
97.7%

Length

2022-09-05T21:39:06.826486image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:06.911125image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
10.01
50.0%
6.01
50.0%

Most occurring characters

ValueCountFrequency (%)
03
42.9%
.2
28.6%
11
 
14.3%
61
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number5
71.4%
Other Punctuation2
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
03
60.0%
11
 
20.0%
61
 
20.0%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
03
42.9%
.2
28.6%
11
 
14.3%
61
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
03
42.9%
.2
28.6%
11
 
14.3%
61
 
14.3%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size816.0 B
https://api.tvmaze.com/episodes/1979245
 
1
https://api.tvmaze.com/episodes/1996349
 
1
https://api.tvmaze.com/episodes/2043301
 
1
https://api.tvmaze.com/episodes/2024910
 
1
https://api.tvmaze.com/episodes/1996355
 
1
Other values (81)
81 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3354
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1979245
2nd rowhttps://api.tvmaze.com/episodes/1981560
3rd rowhttps://api.tvmaze.com/episodes/1986869
4th rowhttps://api.tvmaze.com/episodes/2140386
5th rowhttps://api.tvmaze.com/episodes/1945591

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19792451
 
1.2%
https://api.tvmaze.com/episodes/19963491
 
1.2%
https://api.tvmaze.com/episodes/20433011
 
1.2%
https://api.tvmaze.com/episodes/20249101
 
1.2%
https://api.tvmaze.com/episodes/19963551
 
1.2%
https://api.tvmaze.com/episodes/19963541
 
1.2%
https://api.tvmaze.com/episodes/19963531
 
1.2%
https://api.tvmaze.com/episodes/19963521
 
1.2%
https://api.tvmaze.com/episodes/19963511
 
1.2%
https://api.tvmaze.com/episodes/19963501
 
1.2%
Other values (76)76
88.4%

Length

2022-09-05T21:39:06.981581image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19792451
 
1.2%
https://api.tvmaze.com/episodes/19829141
 
1.2%
https://api.tvmaze.com/episodes/21403861
 
1.2%
https://api.tvmaze.com/episodes/19455911
 
1.2%
https://api.tvmaze.com/episodes/20654401
 
1.2%
https://api.tvmaze.com/episodes/20802231
 
1.2%
https://api.tvmaze.com/episodes/19773151
 
1.2%
https://api.tvmaze.com/episodes/20030921
 
1.2%
https://api.tvmaze.com/episodes/19815011
 
1.2%
https://api.tvmaze.com/episodes/19787791
 
1.2%
Other values (76)76
88.4%

Most occurring characters

ValueCountFrequency (%)
/344
 
10.3%
p258
 
7.7%
s258
 
7.7%
e258
 
7.7%
t258
 
7.7%
o172
 
5.1%
a172
 
5.1%
i172
 
5.1%
.172
 
5.1%
m172
 
5.1%
Other values (16)1118
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2150
64.1%
Other Punctuation602
 
17.9%
Decimal Number602
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p258
12.0%
s258
12.0%
e258
12.0%
t258
12.0%
o172
8.0%
a172
8.0%
i172
8.0%
m172
8.0%
h86
 
4.0%
d86
 
4.0%
Other values (3)258
12.0%
Decimal Number
ValueCountFrequency (%)
1119
19.8%
9103
17.1%
260
10.0%
060
10.0%
549
8.1%
747
 
7.8%
646
 
7.6%
843
 
7.1%
338
 
6.3%
437
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/344
57.1%
.172
28.6%
:86
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2150
64.1%
Common1204
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/344
28.6%
.172
14.3%
1119
 
9.9%
9103
 
8.6%
:86
 
7.1%
260
 
5.0%
060
 
5.0%
549
 
4.1%
747
 
3.9%
646
 
3.8%
Other values (3)118
 
9.8%
Latin
ValueCountFrequency (%)
p258
12.0%
s258
12.0%
e258
12.0%
t258
12.0%
o172
8.0%
a172
8.0%
i172
8.0%
m172
8.0%
h86
 
4.0%
d86
 
4.0%
Other values (3)258
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/344
 
10.3%
p258
 
7.7%
s258
 
7.7%
e258
 
7.7%
t258
 
7.7%
o172
 
5.1%
a172
 
5.1%
i172
 
5.1%
.172
 
5.1%
m172
 
5.1%
Other values (16)1118
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct59
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45885.10465
Minimum802
Maximum63310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:07.075616image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum802
5-th percentile8422.75
Q145115.25
median52108
Q352671.5
95-th percentile58089.5
Maximum63310
Range62508
Interquartile range (IQR)7556.25

Descriptive statistics

Standard deviation14295.38302
Coefficient of variation (CV)0.3115473557
Kurtosis2.647181833
Mean45885.10465
Median Absolute Deviation (MAD)1293
Skewness-1.878492294
Sum3946119
Variance204357975.7
MonotonicityNot monotonic
2022-09-05T21:39:07.187502image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
527308
 
9.3%
524226
 
7.0%
519545
 
5.8%
522724
 
4.7%
521812
 
2.3%
152502
 
2.3%
522872
 
2.3%
588212
 
2.3%
549962
 
2.3%
521592
 
2.3%
Other values (49)51
59.3%
ValueCountFrequency (%)
8021
1.2%
25041
1.2%
60901
1.2%
61461
1.2%
61471
1.2%
152502
2.3%
175841
1.2%
189711
1.2%
224731
1.2%
262681
1.2%
ValueCountFrequency (%)
633101
1.2%
617551
1.2%
588212
2.3%
583671
1.2%
572571
1.2%
570091
1.2%
566551
1.2%
550191
1.2%
549962
2.3%
546101
1.2%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct59
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size816.0 B
https://www.tvmaze.com/shows/52730/fixer
https://www.tvmaze.com/shows/52422/light-speed
 
6
https://www.tvmaze.com/shows/51954/the-runner
 
5
https://www.tvmaze.com/shows/52272/room-2806-the-accusation
 
4
https://www.tvmaze.com/shows/52181/volk
 
2
Other values (54)
61 

Length

Max length79
Median length60
Mean length49.38372093
Min length39

Characters and Unicode

Total characters4247
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)54.7%

Sample

1st rowhttps://www.tvmaze.com/shows/52181/volk
2nd rowhttps://www.tvmaze.com/shows/52181/volk
3rd rowhttps://www.tvmaze.com/shows/52198/kotiki
4th rowhttps://www.tvmaze.com/shows/56655/going-seventeen
5th rowhttps://www.tvmaze.com/shows/50916/my-little-invisible-being

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52730/fixer8
 
9.3%
https://www.tvmaze.com/shows/52422/light-speed6
 
7.0%
https://www.tvmaze.com/shows/51954/the-runner5
 
5.8%
https://www.tvmaze.com/shows/52272/room-2806-the-accusation4
 
4.7%
https://www.tvmaze.com/shows/52181/volk2
 
2.3%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
2.3%
https://www.tvmaze.com/shows/52287/inside-poundland-secrets-from-the-shop-floor2
 
2.3%
https://www.tvmaze.com/shows/58821/tunelis2
 
2.3%
https://www.tvmaze.com/shows/54996/the-silent-criminal2
 
2.3%
https://www.tvmaze.com/shows/52159/to-love2
 
2.3%
Other values (49)51
59.3%

Length

2022-09-05T21:39:07.300242image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52730/fixer8
 
9.3%
https://www.tvmaze.com/shows/52422/light-speed6
 
7.0%
https://www.tvmaze.com/shows/51954/the-runner5
 
5.8%
https://www.tvmaze.com/shows/52272/room-2806-the-accusation4
 
4.7%
https://www.tvmaze.com/shows/54996/the-silent-criminal2
 
2.3%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
2.3%
https://www.tvmaze.com/shows/52159/to-love2
 
2.3%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.3%
https://www.tvmaze.com/shows/58821/tunelis2
 
2.3%
https://www.tvmaze.com/shows/52287/inside-poundland-secrets-from-the-shop-floor2
 
2.3%
Other values (49)51
59.3%

Most occurring characters

ValueCountFrequency (%)
/430
 
10.1%
w358
 
8.4%
t353
 
8.3%
s323
 
7.6%
o246
 
5.8%
e232
 
5.5%
h225
 
5.3%
m204
 
4.8%
.172
 
4.0%
a159
 
3.7%
Other values (30)1545
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2983
70.2%
Other Punctuation688
 
16.2%
Decimal Number442
 
10.4%
Dash Punctuation134
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w358
12.0%
t353
11.8%
s323
10.8%
o246
 
8.2%
e232
 
7.8%
h225
 
7.5%
m204
 
6.8%
a159
 
5.3%
c120
 
4.0%
p113
 
3.8%
Other values (16)650
21.8%
Decimal Number
ValueCountFrequency (%)
587
19.7%
277
17.4%
044
10.0%
144
10.0%
438
8.6%
732
 
7.2%
932
 
7.2%
630
 
6.8%
830
 
6.8%
328
 
6.3%
Other Punctuation
ValueCountFrequency (%)
/430
62.5%
.172
 
25.0%
:86
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2983
70.2%
Common1264
29.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
w358
12.0%
t353
11.8%
s323
10.8%
o246
 
8.2%
e232
 
7.8%
h225
 
7.5%
m204
 
6.8%
a159
 
5.3%
c120
 
4.0%
p113
 
3.8%
Other values (16)650
21.8%
Common
ValueCountFrequency (%)
/430
34.0%
.172
 
13.6%
-134
 
10.6%
587
 
6.9%
:86
 
6.8%
277
 
6.1%
044
 
3.5%
144
 
3.5%
438
 
3.0%
732
 
2.5%
Other values (4)120
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII4247
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/430
 
10.1%
w358
 
8.4%
t353
 
8.3%
s323
 
7.6%
o246
 
5.8%
e232
 
5.5%
h225
 
5.3%
m204
 
4.8%
.172
 
4.0%
a159
 
3.7%
Other values (30)1545
36.4%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct59
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size816.0 B
Fixer
Light Speed
 
6
The Runner
 
5
Room 2806: The Accusation
 
4
Волк
 
2
Other values (54)
61 

Length

Max length45
Median length21
Mean length14.62790698
Min length4

Characters and Unicode

Total characters1258
Distinct characters92
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)54.7%

Sample

1st rowВолк
2nd rowВолк
3rd rowКотики
4th rowGoing Seventeen
5th rowMy Little Invisible Being

Common Values

ValueCountFrequency (%)
Fixer8
 
9.3%
Light Speed6
 
7.0%
The Runner5
 
5.8%
Room 2806: The Accusation4
 
4.7%
Волк2
 
2.3%
The Young Turks2
 
2.3%
Inside Poundland: Secrets from the Shop Floor2
 
2.3%
Tunelis2
 
2.3%
The Silent Criminal2
 
2.3%
To Love2
 
2.3%
Other values (49)51
59.3%

Length

2022-09-05T21:39:07.403224image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the22
 
10.0%
fixer8
 
3.6%
speed6
 
2.7%
light6
 
2.7%
runner5
 
2.3%
of5
 
2.3%
accusation4
 
1.8%
love4
 
1.8%
room4
 
1.8%
28064
 
1.8%
Other values (128)152
69.1%

Most occurring characters

ValueCountFrequency (%)
e134
 
10.7%
134
 
10.7%
n73
 
5.8%
o63
 
5.0%
i60
 
4.8%
r58
 
4.6%
t51
 
4.1%
h50
 
4.0%
a48
 
3.8%
s41
 
3.3%
Other values (82)546
43.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter884
70.3%
Uppercase Letter208
 
16.5%
Space Separator134
 
10.7%
Decimal Number18
 
1.4%
Other Punctuation14
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e134
15.2%
n73
 
8.3%
o63
 
7.1%
i60
 
6.8%
r58
 
6.6%
t51
 
5.8%
h50
 
5.7%
a48
 
5.4%
s41
 
4.6%
u38
 
4.3%
Other values (39)268
30.3%
Uppercase Letter
ValueCountFrequency (%)
T39
18.8%
S21
10.1%
R18
 
8.7%
A16
 
7.7%
F15
 
7.2%
M11
 
5.3%
L11
 
5.3%
C10
 
4.8%
W9
 
4.3%
B8
 
3.8%
Other values (21)50
24.0%
Other Punctuation
ValueCountFrequency (%)
:6
42.9%
'3
21.4%
.2
 
14.3%
!1
 
7.1%
?1
 
7.1%
,1
 
7.1%
Decimal Number
ValueCountFrequency (%)
05
27.8%
64
22.2%
84
22.2%
24
22.2%
31
 
5.6%
Space Separator
ValueCountFrequency (%)
134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1011
80.4%
Common166
 
13.2%
Cyrillic81
 
6.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e134
 
13.3%
n73
 
7.2%
o63
 
6.2%
i60
 
5.9%
r58
 
5.7%
t51
 
5.0%
h50
 
4.9%
a48
 
4.7%
s41
 
4.1%
T39
 
3.9%
Other values (40)394
39.0%
Cyrillic
ValueCountFrequency (%)
о9
 
11.1%
и7
 
8.6%
е6
 
7.4%
к5
 
6.2%
т5
 
6.2%
а5
 
6.2%
п5
 
6.2%
н5
 
6.2%
р4
 
4.9%
В4
 
4.9%
Other values (20)26
32.1%
Common
ValueCountFrequency (%)
134
80.7%
:6
 
3.6%
05
 
3.0%
64
 
2.4%
84
 
2.4%
24
 
2.4%
'3
 
1.8%
.2
 
1.2%
!1
 
0.6%
31
 
0.6%
Other values (2)2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII1174
93.3%
Cyrillic81
 
6.4%
None3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e134
 
11.4%
134
 
11.4%
n73
 
6.2%
o63
 
5.4%
i60
 
5.1%
r58
 
4.9%
t51
 
4.3%
h50
 
4.3%
a48
 
4.1%
s41
 
3.5%
Other values (49)462
39.4%
Cyrillic
ValueCountFrequency (%)
о9
 
11.1%
и7
 
8.6%
е6
 
7.4%
к5
 
6.2%
т5
 
6.2%
а5
 
6.2%
п5
 
6.2%
н5
 
6.2%
р4
 
4.9%
В4
 
4.9%
Other values (20)26
32.1%
None
ValueCountFrequency (%)
ø1
33.3%
ä1
33.3%
Ç1
33.3%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size816.0 B
Scripted
40 
Documentary
16 
Talk Show
10 
Reality
Animation
Other values (4)

Length

Max length11
Median length9
Mean length8.488372093
Min length4

Characters and Unicode

Total characters730
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.3%

Sample

1st rowScripted
2nd rowScripted
3rd rowScripted
4th rowVariety
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted40
46.5%
Documentary16
 
18.6%
Talk Show10
 
11.6%
Reality7
 
8.1%
Animation6
 
7.0%
News3
 
3.5%
Variety2
 
2.3%
Game Show1
 
1.2%
Sports1
 
1.2%

Length

2022-09-05T21:39:07.498138image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:07.605928image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted40
41.2%
documentary16
 
16.5%
show11
 
11.3%
talk10
 
10.3%
reality7
 
7.2%
animation6
 
6.2%
news3
 
3.1%
variety2
 
2.1%
game1
 
1.0%
sports1
 
1.0%

Most occurring characters

ValueCountFrequency (%)
t72
 
9.9%
e69
 
9.5%
i61
 
8.4%
r59
 
8.1%
c56
 
7.7%
S52
 
7.1%
a42
 
5.8%
p41
 
5.6%
d40
 
5.5%
o34
 
4.7%
Other values (17)204
27.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter622
85.2%
Uppercase Letter97
 
13.3%
Space Separator11
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t72
11.6%
e69
11.1%
i61
9.8%
r59
9.5%
c56
9.0%
a42
 
6.8%
p41
 
6.6%
d40
 
6.4%
o34
 
5.5%
n28
 
4.5%
Other values (8)120
19.3%
Uppercase Letter
ValueCountFrequency (%)
S52
53.6%
D16
 
16.5%
T10
 
10.3%
R7
 
7.2%
A6
 
6.2%
N3
 
3.1%
V2
 
2.1%
G1
 
1.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin719
98.5%
Common11
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t72
 
10.0%
e69
 
9.6%
i61
 
8.5%
r59
 
8.2%
c56
 
7.8%
S52
 
7.2%
a42
 
5.8%
p41
 
5.7%
d40
 
5.6%
o34
 
4.7%
Other values (16)193
26.8%
Common
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII730
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t72
 
9.9%
e69
 
9.5%
i61
 
8.4%
r59
 
8.1%
c56
 
7.7%
S52
 
7.1%
a42
 
5.8%
p41
 
5.6%
d40
 
5.5%
o34
 
4.7%
Other values (17)204
27.9%

_embedded.show.language
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)16.7%
Missing2
Missing (%)2.3%
Memory size816.0 B
English
31 
Chinese
17 
Arabic
10 
Russian
Korean
 
3
Other values (9)
14 

Length

Max length10
Median length7
Mean length6.857142857
Min length4

Characters and Unicode

Total characters576
Distinct characters31
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)6.0%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowKorean
5th rowChinese

Common Values

ValueCountFrequency (%)
English31
36.0%
Chinese17
19.8%
Arabic10
 
11.6%
Russian9
 
10.5%
Korean3
 
3.5%
Norwegian3
 
3.5%
Dutch2
 
2.3%
Thai2
 
2.3%
Latvian2
 
2.3%
Portuguese1
 
1.2%
Other values (4)4
 
4.7%
(Missing)2
 
2.3%

Length

2022-09-05T21:39:07.699633image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english31
36.9%
chinese17
20.2%
arabic10
 
11.9%
russian9
 
10.7%
korean3
 
3.6%
norwegian3
 
3.6%
dutch2
 
2.4%
thai2
 
2.4%
latvian2
 
2.4%
portuguese1
 
1.2%
Other values (4)4
 
4.8%

Most occurring characters

ValueCountFrequency (%)
i78
13.5%
s69
12.0%
n68
11.8%
h55
9.5%
e44
 
7.6%
g35
 
6.1%
a34
 
5.9%
E31
 
5.4%
l31
 
5.4%
r19
 
3.3%
Other values (21)112
19.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter492
85.4%
Uppercase Letter84
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i78
15.9%
s69
14.0%
n68
13.8%
h55
11.2%
e44
8.9%
g35
7.1%
a34
6.9%
l31
 
6.3%
r19
 
3.9%
u15
 
3.0%
Other values (9)44
8.9%
Uppercase Letter
ValueCountFrequency (%)
E31
36.9%
C17
20.2%
A10
 
11.9%
R9
 
10.7%
N3
 
3.6%
K3
 
3.6%
T3
 
3.6%
L3
 
3.6%
D2
 
2.4%
P1
 
1.2%
Other values (2)2
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Latin576
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i78
13.5%
s69
12.0%
n68
11.8%
h55
9.5%
e44
 
7.6%
g35
 
6.1%
a34
 
5.9%
E31
 
5.4%
l31
 
5.4%
r19
 
3.3%
Other values (21)112
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII576
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i78
13.5%
s69
12.0%
n68
11.8%
h55
9.5%
e44
 
7.6%
g35
 
6.1%
a34
 
5.9%
E31
 
5.4%
l31
 
5.4%
r19
 
3.3%
Other values (21)112
19.4%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size816.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size816.0 B
Ended
45 
Running
33 
To Be Determined

Length

Max length16
Median length5
Mean length6.790697674
Min length5

Characters and Unicode

Total characters584
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowEnded
3rd rowEnded
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended45
52.3%
Running33
38.4%
To Be Determined8
 
9.3%

Length

2022-09-05T21:39:07.802922image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:07.912475image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ended45
44.1%
running33
32.4%
to8
 
7.8%
be8
 
7.8%
determined8
 
7.8%

Most occurring characters

ValueCountFrequency (%)
n152
26.0%
d98
16.8%
e77
13.2%
E45
 
7.7%
i41
 
7.0%
R33
 
5.7%
u33
 
5.7%
g33
 
5.7%
16
 
2.7%
T8
 
1.4%
Other values (6)48
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter466
79.8%
Uppercase Letter102
 
17.5%
Space Separator16
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n152
32.6%
d98
21.0%
e77
16.5%
i41
 
8.8%
u33
 
7.1%
g33
 
7.1%
o8
 
1.7%
t8
 
1.7%
r8
 
1.7%
m8
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
E45
44.1%
R33
32.4%
T8
 
7.8%
B8
 
7.8%
D8
 
7.8%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin568
97.3%
Common16
 
2.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n152
26.8%
d98
17.3%
e77
13.6%
E45
 
7.9%
i41
 
7.2%
R33
 
5.8%
u33
 
5.8%
g33
 
5.8%
T8
 
1.4%
o8
 
1.4%
Other values (5)40
 
7.0%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n152
26.0%
d98
16.8%
e77
13.2%
E45
 
7.7%
i41
 
7.0%
R33
 
5.7%
u33
 
5.7%
g33
 
5.7%
16
 
2.7%
T8
 
1.4%
Other values (6)48
 
8.2%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct22
Distinct (%)34.4%
Missing22
Missing (%)25.6%
Infinite0
Infinite (%)0.0%
Mean43.15625
Minimum2
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:08.001015image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.75
Q118
median42.5
Q360
95-th percentile120
Maximum180
Range178
Interquartile range (IQR)42

Descriptive statistics

Standard deviation33.51721602
Coefficient of variation (CV)0.7766480179
Kurtosis4.291470055
Mean43.15625
Median Absolute Deviation (MAD)17.5
Skewness1.791351974
Sum2762
Variance1123.40377
MonotonicityNot monotonic
2022-09-05T21:39:08.114545image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
6012
14.0%
458
 
9.3%
188
 
9.3%
304
 
4.7%
53
 
3.5%
103
 
3.5%
203
 
3.5%
503
 
3.5%
1203
 
3.5%
512
 
2.3%
Other values (12)15
17.4%
(Missing)22
25.6%
ValueCountFrequency (%)
21
 
1.2%
53
 
3.5%
103
 
3.5%
121
 
1.2%
152
 
2.3%
188
9.3%
203
 
3.5%
221
 
1.2%
231
 
1.2%
252
 
2.3%
ValueCountFrequency (%)
1801
 
1.2%
1301
 
1.2%
1203
 
3.5%
901
 
1.2%
6012
14.0%
512
 
2.3%
503
 
3.5%
481
 
1.2%
458
9.3%
401
 
1.2%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct29
Distinct (%)34.1%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean39.47058824
Minimum2
Maximum181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:08.225414image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8.2
Q117
median30
Q350
95-th percentile114
Maximum181
Range179
Interquartile range (IQR)33

Descriptive statistics

Standard deviation31.1836298
Coefficient of variation (CV)0.7900472528
Kurtosis5.326116937
Mean39.47058824
Median Absolute Deviation (MAD)15
Skewness1.954591128
Sum3355
Variance972.4187675
MonotonicityNot monotonic
2022-09-05T21:39:08.336744image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
6010
 
11.6%
509
 
10.5%
178
 
9.3%
458
 
9.3%
217
 
8.1%
304
 
4.7%
104
 
4.7%
254
 
4.7%
53
 
3.5%
203
 
3.5%
Other values (19)25
29.1%
ValueCountFrequency (%)
21
 
1.2%
53
 
3.5%
81
 
1.2%
91
 
1.2%
104
4.7%
122
 
2.3%
141
 
1.2%
152
 
2.3%
161
 
1.2%
178
9.3%
ValueCountFrequency (%)
1811
 
1.2%
1301
 
1.2%
1203
 
3.5%
901
 
1.2%
771
 
1.2%
761
 
1.2%
6010
11.6%
509
10.5%
481
 
1.2%
458
9.3%

_embedded.show.premiered
Categorical

HIGH CORRELATION

Distinct43
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size816.0 B
2020-12-07
25 
2020-11-23
2020-11-16
2020-11-09
 
4
2020-11-30
 
3
Other values (38)
41 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters860
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)40.7%

Sample

1st row2020-12-07
2nd row2020-12-07
3rd row2020-11-30
4th row2017-06-12
5th row2020-10-05

Common Values

ValueCountFrequency (%)
2020-12-0725
29.1%
2020-11-237
 
8.1%
2020-11-166
 
7.0%
2020-11-094
 
4.7%
2020-11-303
 
3.5%
2013-12-242
 
2.3%
2020-11-192
 
2.3%
2020-10-052
 
2.3%
1993-01-111
 
1.2%
2017-10-091
 
1.2%
Other values (33)33
38.4%

Length

2022-09-05T21:39:08.439186image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-0725
29.1%
2020-11-237
 
8.1%
2020-11-166
 
7.0%
2020-11-094
 
4.7%
2020-11-303
 
3.5%
2013-12-242
 
2.3%
2020-11-192
 
2.3%
2020-10-052
 
2.3%
2020-09-091
 
1.2%
2017-06-121
 
1.2%
Other values (33)33
38.4%

Most occurring characters

ValueCountFrequency (%)
0229
26.6%
2194
22.6%
-172
20.0%
1144
16.7%
734
 
4.0%
927
 
3.1%
321
 
2.4%
812
 
1.4%
611
 
1.3%
48
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number688
80.0%
Dash Punctuation172
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0229
33.3%
2194
28.2%
1144
20.9%
734
 
4.9%
927
 
3.9%
321
 
3.1%
812
 
1.7%
611
 
1.6%
48
 
1.2%
58
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
-172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common860
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0229
26.6%
2194
22.6%
-172
20.0%
1144
16.7%
734
 
4.0%
927
 
3.1%
321
 
2.4%
812
 
1.4%
611
 
1.3%
48
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0229
26.6%
2194
22.6%
-172
20.0%
1144
16.7%
734
 
4.0%
927
 
3.1%
321
 
2.4%
812
 
1.4%
611
 
1.3%
48
 
0.9%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)31.1%
Missing41
Missing (%)47.7%
Memory size816.0 B
2020-12-07
19 
2020-12-14
2020-12-28
2021-01-18
2020-12-30
Other values (9)
11 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters450
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)15.6%

Sample

1st row2020-12-28
2nd row2020-12-28
3rd row2020-12-11
4th row2020-12-24
5th row2020-12-10

Common Values

ValueCountFrequency (%)
2020-12-0719
22.1%
2020-12-148
 
9.3%
2020-12-283
 
3.5%
2021-01-182
 
2.3%
2020-12-302
 
2.3%
2020-12-162
 
2.3%
2020-12-232
 
2.3%
2020-12-111
 
1.2%
2020-12-241
 
1.2%
2020-12-101
 
1.2%
Other values (4)4
 
4.7%
(Missing)41
47.7%

Length

2022-09-05T21:39:08.530150image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-0719
42.2%
2020-12-148
17.8%
2020-12-283
 
6.7%
2021-01-182
 
4.4%
2020-12-302
 
4.4%
2020-12-162
 
4.4%
2020-12-232
 
4.4%
2020-12-111
 
2.2%
2020-12-241
 
2.2%
2020-12-101
 
2.2%
Other values (4)4
 
8.9%

Most occurring characters

ValueCountFrequency (%)
2141
31.3%
0112
24.9%
-90
20.0%
165
14.4%
720
 
4.4%
49
 
2.0%
86
 
1.3%
34
 
0.9%
63
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number360
80.0%
Dash Punctuation90
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2141
39.2%
0112
31.1%
165
18.1%
720
 
5.6%
49
 
2.5%
86
 
1.7%
34
 
1.1%
63
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
-90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common450
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2141
31.3%
0112
24.9%
-90
20.0%
165
14.4%
720
 
4.4%
49
 
2.0%
86
 
1.3%
34
 
0.9%
63
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2141
31.3%
0112
24.9%
-90
20.0%
165
14.4%
720
 
4.4%
49
 
2.0%
86
 
1.3%
34
 
0.9%
63
 
0.7%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct55
Distinct (%)70.5%
Missing8
Missing (%)9.3%
Memory size816.0 B
https://shahid.mbc.net/en/series/Fixer/series-820315
https://www.youtube.com/playlist?list=PL6uC-XGZC7X7nu1ycW1YGbl-wErl027uc
https://www.netflix.com/title/81068760
 
4
https://premier.one/show/12339
 
2
https://www.tytnetwork.com
 
2
Other values (50)
56 

Length

Max length130
Median length74.5
Mean length52.96153846
Min length18

Characters and Unicode

Total characters4131
Distinct characters76
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)56.4%

Sample

1st rowhttps://premier.one/show/12339
2nd rowhttps://premier.one/show/12339
3rd rowhttp://epic-media.ru/project/kotiki
4th rowhttps://www.bilibili.com/bangumi/media/md28229943/
5th rowhttps://v.qq.com/detail/5/5cuf8ahvxvm2587.html

Common Values

ValueCountFrequency (%)
https://shahid.mbc.net/en/series/Fixer/series-8203158
 
9.3%
https://www.youtube.com/playlist?list=PL6uC-XGZC7X7nu1ycW1YGbl-wErl027uc6
 
7.0%
https://www.netflix.com/title/810687604
 
4.7%
https://premier.one/show/123392
 
2.3%
https://www.tytnetwork.com2
 
2.3%
https://www.channel4.com/programmes/inside-poundland-secrets-from-the-shop-floor2
 
2.3%
https://go3.tv/series/tunnel,serial-22014172
 
2.3%
https://www.iqiyi.com/a_je0t80m6td.html2
 
2.3%
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=12
 
2.3%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
2.3%
Other values (45)46
53.5%
(Missing)8
 
9.3%

Length

2022-09-05T21:39:08.644625image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://shahid.mbc.net/en/series/fixer/series-8203158
 
10.3%
https://www.youtube.com/playlist?list=pl6uc-xgzc7x7nu1ycw1ygbl-werl027uc6
 
7.7%
https://www.netflix.com/title/810687604
 
5.1%
https://www.iqiyi.com/a_je0t80m6td.html2
 
2.6%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
2.6%
https://so.youku.com/search_video/q_%20%e6%9c%80%e5%88%9d%e7%9a%84%e7%9b%b8%e9%81%87?searchfrom=12
 
2.6%
https://www.iqiyi.com/a_19rrhskr95.html2
 
2.6%
https://go3.tv/series/tunnel,serial-22014172
 
2.6%
https://www.channel4.com/programmes/inside-poundland-secrets-from-the-shop-floor2
 
2.6%
https://www.tytnetwork.com2
 
2.6%
Other values (45)46
59.0%

Most occurring characters

ValueCountFrequency (%)
/331
 
8.0%
t311
 
7.5%
e246
 
6.0%
s236
 
5.7%
o165
 
4.0%
w163
 
3.9%
h162
 
3.9%
.147
 
3.6%
i145
 
3.5%
r136
 
3.3%
Other values (66)2089
50.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2677
64.8%
Other Punctuation643
 
15.6%
Decimal Number427
 
10.3%
Uppercase Letter247
 
6.0%
Dash Punctuation92
 
2.2%
Math Symbol29
 
0.7%
Connector Punctuation16
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t311
 
11.6%
e246
 
9.2%
s236
 
8.8%
o165
 
6.2%
w163
 
6.1%
h162
 
6.1%
i145
 
5.4%
r136
 
5.1%
p124
 
4.6%
c117
 
4.4%
Other values (16)872
32.6%
Uppercase Letter
ValueCountFrequency (%)
C26
 
10.5%
E25
 
10.1%
G17
 
6.9%
L15
 
6.1%
X15
 
6.1%
B14
 
5.7%
P14
 
5.7%
F13
 
5.3%
A13
 
5.3%
Y12
 
4.9%
Other values (16)83
33.6%
Decimal Number
ValueCountFrequency (%)
158
13.6%
055
12.9%
848
11.2%
747
11.0%
244
10.3%
638
8.9%
437
8.7%
535
8.2%
933
7.7%
332
7.5%
Other Punctuation
ValueCountFrequency (%)
/331
51.5%
.147
22.9%
:78
 
12.1%
%57
 
8.9%
?15
 
2.3%
&10
 
1.6%
,3
 
0.5%
#1
 
0.2%
!1
 
0.2%
Math Symbol
ValueCountFrequency (%)
=26
89.7%
+2
 
6.9%
~1
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
-92
100.0%
Connector Punctuation
ValueCountFrequency (%)
_16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2924
70.8%
Common1207
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t311
 
10.6%
e246
 
8.4%
s236
 
8.1%
o165
 
5.6%
w163
 
5.6%
h162
 
5.5%
i145
 
5.0%
r136
 
4.7%
p124
 
4.2%
c117
 
4.0%
Other values (42)1119
38.3%
Common
ValueCountFrequency (%)
/331
27.4%
.147
12.2%
-92
 
7.6%
:78
 
6.5%
158
 
4.8%
%57
 
4.7%
055
 
4.6%
848
 
4.0%
747
 
3.9%
244
 
3.6%
Other values (14)250
20.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII4131
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/331
 
8.0%
t311
 
7.5%
e246
 
6.0%
s236
 
5.7%
o165
 
4.0%
w163
 
3.9%
h162
 
3.9%
.147
 
3.6%
i145
 
3.5%
r136
 
3.3%
Other values (66)2089
50.6%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size816.0 B
62 
20:00
12 
10:00
 
3
21:00
 
2
08:00
 
1
Other values (6)
 
6

Length

Max length5
Median length0
Mean length1.395348837
Min length0

Characters and Unicode

Total characters120
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)8.1%

Sample

1st row
2nd row
3rd row10:00
4th row08:00
5th row12:00

Common Values

ValueCountFrequency (%)
62
72.1%
20:0012
 
14.0%
10:003
 
3.5%
21:002
 
2.3%
08:001
 
1.2%
12:001
 
1.2%
06:001
 
1.2%
17:351
 
1.2%
00:001
 
1.2%
19:001
 
1.2%

Length

2022-09-05T21:39:08.775013image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0012
50.0%
10:003
 
12.5%
21:002
 
8.3%
08:001
 
4.2%
12:001
 
4.2%
06:001
 
4.2%
17:351
 
4.2%
00:001
 
4.2%
19:001
 
4.2%
20:151
 
4.2%

Most occurring characters

ValueCountFrequency (%)
064
53.3%
:24
 
20.0%
216
 
13.3%
19
 
7.5%
52
 
1.7%
81
 
0.8%
61
 
0.8%
71
 
0.8%
31
 
0.8%
91
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number96
80.0%
Other Punctuation24
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
064
66.7%
216
 
16.7%
19
 
9.4%
52
 
2.1%
81
 
1.0%
61
 
1.0%
71
 
1.0%
31
 
1.0%
91
 
1.0%
Other Punctuation
ValueCountFrequency (%)
:24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common120
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
064
53.3%
:24
 
20.0%
216
 
13.3%
19
 
7.5%
52
 
1.7%
81
 
0.8%
61
 
0.8%
71
 
0.8%
31
 
0.8%
91
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
064
53.3%
:24
 
20.0%
216
 
13.3%
19
 
7.5%
52
 
1.7%
81
 
0.8%
61
 
0.8%
71
 
0.8%
31
 
0.8%
91
 
0.8%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size816.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)66.7%
Missing83
Missing (%)96.5%
Memory size816.0 B
7.2
7.5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row7.2
2nd row7.2
3rd row7.5

Common Values

ValueCountFrequency (%)
7.22
 
2.3%
7.51
 
1.2%
(Missing)83
96.5%

Length

2022-09-05T21:39:08.877659image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:08.972117image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.22
66.7%
7.51
33.3%

Most occurring characters

ValueCountFrequency (%)
73
33.3%
.3
33.3%
22
22.2%
51
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
66.7%
Other Punctuation3
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
73
50.0%
22
33.3%
51
 
16.7%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
73
33.3%
.3
33.3%
22
22.2%
51
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
73
33.3%
.3
33.3%
22
22.2%
51
 
11.1%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct39
Distinct (%)45.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.74418605
Minimum1
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:09.077373image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q113.25
median21
Q334
95-th percentile74.25
Maximum95
Range94
Interquartile range (IQR)20.75

Descriptive statistics

Standard deviation21.71103598
Coefficient of variation (CV)0.8118039541
Kurtosis1.490021398
Mean26.74418605
Median Absolute Deviation (MAD)10
Skewness1.378511665
Sum2300
Variance471.3690834
MonotonicityNot monotonic
2022-09-05T21:39:09.203593image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1515
17.4%
38
 
9.3%
135
 
5.8%
244
 
4.7%
424
 
4.7%
344
 
4.7%
213
 
3.5%
333
 
3.5%
73
 
3.5%
283
 
3.5%
Other values (29)34
39.5%
ValueCountFrequency (%)
11
 
1.2%
38
9.3%
41
 
1.2%
51
 
1.2%
73
 
3.5%
82
 
2.3%
111
 
1.2%
135
 
5.8%
141
 
1.2%
1515
17.4%
ValueCountFrequency (%)
951
1.2%
881
1.2%
841
1.2%
831
1.2%
751
1.2%
721
1.2%
691
1.2%
671
1.2%
641
1.2%
601
1.2%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing86
Missing (%)100.0%
Memory size816.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct35
Distinct (%)41.2%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean177.0823529
Minimum1
Maximum518
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:09.314578image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.4
Q121
median102
Q3379
95-th percentile494.2
Maximum518
Range517
Interquartile range (IQR)358

Descriptive statistics

Standard deviation174.7255816
Coefficient of variation (CV)0.9866910997
Kurtosis-1.214822456
Mean177.0823529
Median Absolute Deviation (MAD)81
Skewness0.6517833018
Sum15052
Variance30529.02885
MonotonicityNot monotonic
2022-09-05T21:39:09.439783image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
2116
18.6%
37910
 
11.6%
436
 
7.0%
4285
 
5.8%
675
 
5.8%
14
 
4.7%
1044
 
4.7%
5183
 
3.5%
152
 
2.3%
322
 
2.3%
Other values (25)28
32.6%
ValueCountFrequency (%)
14
 
4.7%
31
 
1.2%
152
 
2.3%
2116
18.6%
301
 
1.2%
322
 
2.3%
401
 
1.2%
436
 
7.0%
511
 
1.2%
522
 
2.3%
ValueCountFrequency (%)
5183
 
3.5%
5161
 
1.2%
5101
 
1.2%
4311
 
1.2%
4285
5.8%
4161
 
1.2%
4131
 
1.2%
37910
11.6%
3681
 
1.2%
3671
 
1.2%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct35
Distinct (%)41.2%
Missing1
Missing (%)1.2%
Memory size816.0 B
YouTube
16 
Shahid
10 
YouTube Premium
TVB Anywhere
iQIYI
Other values (30)
43 

Length

Max length20
Median length15
Mean length8.105882353
Min length3

Characters and Unicode

Total characters689
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)25.9%

Sample

1st rowPremier
2nd rowPremier
3rd rowEpic Media
4th rowV LIVE
5th rowBilibili

Common Values

ValueCountFrequency (%)
YouTube16
18.6%
Shahid10
 
11.6%
YouTube Premium6
 
7.0%
TVB Anywhere5
 
5.8%
iQIYI5
 
5.8%
Netflix4
 
4.7%
Tencent QQ4
 
4.7%
Go33
 
3.5%
WWE Network2
 
2.3%
Rooster Teeth2
 
2.3%
Other values (25)28
32.6%

Length

2022-09-05T21:39:09.565613image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube22
18.5%
shahid10
 
8.4%
premium6
 
5.0%
tvb5
 
4.2%
anywhere5
 
4.2%
iqiyi5
 
4.2%
netflix4
 
3.4%
tencent4
 
3.4%
qq4
 
3.4%
go33
 
2.5%
Other values (40)51
42.9%

Most occurring characters

ValueCountFrequency (%)
e78
 
11.3%
u59
 
8.6%
T42
 
6.1%
o41
 
6.0%
i40
 
5.8%
34
 
4.9%
Y29
 
4.2%
h29
 
4.2%
b25
 
3.6%
r25
 
3.6%
Other values (39)287
41.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter454
65.9%
Uppercase Letter192
27.9%
Space Separator34
 
4.9%
Decimal Number6
 
0.9%
Math Symbol2
 
0.3%
Other Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e78
17.2%
u59
13.0%
o41
9.0%
i40
 
8.8%
h29
 
6.4%
b25
 
5.5%
r25
 
5.5%
t22
 
4.8%
a19
 
4.2%
m16
 
3.5%
Other values (12)100
22.0%
Uppercase Letter
ValueCountFrequency (%)
T42
21.9%
Y29
15.1%
V15
 
7.8%
P14
 
7.3%
Q13
 
6.8%
I11
 
5.7%
S10
 
5.2%
N9
 
4.7%
A8
 
4.2%
B7
 
3.6%
Other values (11)34
17.7%
Decimal Number
ValueCountFrequency (%)
33
50.0%
42
33.3%
21
 
16.7%
Space Separator
ValueCountFrequency (%)
34
100.0%
Math Symbol
ValueCountFrequency (%)
+2
100.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin646
93.8%
Common43
 
6.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e78
 
12.1%
u59
 
9.1%
T42
 
6.5%
o41
 
6.3%
i40
 
6.2%
Y29
 
4.5%
h29
 
4.5%
b25
 
3.9%
r25
 
3.9%
t22
 
3.4%
Other values (33)256
39.6%
Common
ValueCountFrequency (%)
34
79.1%
33
 
7.0%
+2
 
4.7%
42
 
4.7%
21
 
2.3%
.1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII689
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e78
 
11.3%
u59
 
8.6%
T42
 
6.1%
o41
 
6.0%
i40
 
5.8%
34
 
4.9%
Y29
 
4.2%
h29
 
4.2%
b25
 
3.6%
r25
 
3.6%
Other values (39)287
41.7%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)33.3%
Missing53
Missing (%)61.6%
Memory size816.0 B
China
United States
Hong Kong
Russian Federation
Korea, Republic of
Other values (6)

Length

Max length18
Median length13
Mean length10.45454545
Min length5

Characters and Unicode

Total characters345
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)12.1%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowRussian Federation
4th rowKorea, Republic of
5th rowChina

Common Values

ValueCountFrequency (%)
China7
 
8.1%
United States7
 
8.1%
Hong Kong5
 
5.8%
Russian Federation4
 
4.7%
Korea, Republic of2
 
2.3%
Norway2
 
2.3%
United Kingdom2
 
2.3%
Belgium1
 
1.2%
Brazil1
 
1.2%
Turkey1
 
1.2%
(Missing)53
61.6%

Length

2022-09-05T21:39:09.679607image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
united9
16.4%
china7
12.7%
states7
12.7%
hong5
9.1%
kong5
9.1%
russian4
7.3%
federation4
7.3%
korea2
 
3.6%
republic2
 
3.6%
of2
 
3.6%
Other values (6)8
14.5%

Most occurring characters

ValueCountFrequency (%)
n37
 
10.7%
e31
 
9.0%
i30
 
8.7%
a28
 
8.1%
t27
 
7.8%
22
 
6.4%
o22
 
6.4%
d15
 
4.3%
s15
 
4.3%
g13
 
3.8%
Other values (25)105
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter268
77.7%
Uppercase Letter53
 
15.4%
Space Separator22
 
6.4%
Other Punctuation2
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n37
13.8%
e31
11.6%
i30
11.2%
a28
10.4%
t27
10.1%
o22
8.2%
d15
 
5.6%
s15
 
5.6%
g13
 
4.9%
r11
 
4.1%
Other values (12)39
14.6%
Uppercase Letter
ValueCountFrequency (%)
K9
17.0%
U9
17.0%
C7
13.2%
S7
13.2%
R6
11.3%
H5
9.4%
F4
7.5%
N2
 
3.8%
B2
 
3.8%
T1
 
1.9%
Space Separator
ValueCountFrequency (%)
22
100.0%
Other Punctuation
ValueCountFrequency (%)
,2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin321
93.0%
Common24
 
7.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n37
11.5%
e31
 
9.7%
i30
 
9.3%
a28
 
8.7%
t27
 
8.4%
o22
 
6.9%
d15
 
4.7%
s15
 
4.7%
g13
 
4.0%
r11
 
3.4%
Other values (23)92
28.7%
Common
ValueCountFrequency (%)
22
91.7%
,2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII345
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n37
 
10.7%
e31
 
9.0%
i30
 
8.7%
a28
 
8.1%
t27
 
7.8%
22
 
6.4%
o22
 
6.4%
d15
 
4.3%
s15
 
4.3%
g13
 
3.8%
Other values (25)105
30.4%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)33.3%
Missing53
Missing (%)61.6%
Memory size816.0 B
CN
US
HK
RU
KR
Other values (6)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters66
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)12.1%

Sample

1st rowRU
2nd rowRU
3rd rowRU
4th rowKR
5th rowCN

Common Values

ValueCountFrequency (%)
CN7
 
8.1%
US7
 
8.1%
HK5
 
5.8%
RU4
 
4.7%
KR2
 
2.3%
NO2
 
2.3%
GB2
 
2.3%
BE1
 
1.2%
BR1
 
1.2%
TR1
 
1.2%
(Missing)53
61.6%

Length

2022-09-05T21:39:09.773204image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn7
21.2%
us7
21.2%
hk5
15.2%
ru4
12.1%
kr2
 
6.1%
no2
 
6.1%
gb2
 
6.1%
be1
 
3.0%
br1
 
3.0%
tr1
 
3.0%

Most occurring characters

ValueCountFrequency (%)
U11
16.7%
N9
13.6%
R8
12.1%
C7
10.6%
S7
10.6%
K7
10.6%
H5
7.6%
B4
 
6.1%
O2
 
3.0%
G2
 
3.0%
Other values (3)4
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter66
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U11
16.7%
N9
13.6%
R8
12.1%
C7
10.6%
S7
10.6%
K7
10.6%
H5
7.6%
B4
 
6.1%
O2
 
3.0%
G2
 
3.0%
Other values (3)4
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Latin66
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U11
16.7%
N9
13.6%
R8
12.1%
C7
10.6%
S7
10.6%
K7
10.6%
H5
7.6%
B4
 
6.1%
O2
 
3.0%
G2
 
3.0%
Other values (3)4
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U11
16.7%
N9
13.6%
R8
12.1%
C7
10.6%
S7
10.6%
K7
10.6%
H5
7.6%
B4
 
6.1%
O2
 
3.0%
G2
 
3.0%
Other values (3)4
 
6.1%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)33.3%
Missing53
Missing (%)61.6%
Memory size816.0 B
Asia/Shanghai
America/New_York
Asia/Hong_Kong
Asia/Kamchatka
Asia/Seoul
Other values (6)

Length

Max length16
Median length15
Mean length13.84848485
Min length10

Characters and Unicode

Total characters457
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)12.1%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Seoul
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai7
 
8.1%
America/New_York7
 
8.1%
Asia/Hong_Kong5
 
5.8%
Asia/Kamchatka4
 
4.7%
Asia/Seoul2
 
2.3%
Europe/Oslo2
 
2.3%
Europe/London2
 
2.3%
Europe/Brussels1
 
1.2%
America/Noronha1
 
1.2%
Europe/Istanbul1
 
1.2%
(Missing)53
61.6%

Length

2022-09-05T21:39:09.881257image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai7
21.2%
america/new_york7
21.2%
asia/hong_kong5
15.2%
asia/kamchatka4
12.1%
asia/seoul2
 
6.1%
europe/oslo2
 
6.1%
europe/london2
 
6.1%
europe/brussels1
 
3.0%
america/noronha1
 
3.0%
europe/istanbul1
 
3.0%

Most occurring characters

ValueCountFrequency (%)
a54
 
11.8%
o34
 
7.4%
i34
 
7.4%
/33
 
7.2%
A26
 
5.7%
e26
 
5.7%
n25
 
5.5%
s25
 
5.5%
r24
 
5.3%
h19
 
4.2%
Other values (22)157
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter334
73.1%
Uppercase Letter78
 
17.1%
Other Punctuation33
 
7.2%
Connector Punctuation12
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a54
16.2%
o34
10.2%
i34
10.2%
e26
7.8%
n25
 
7.5%
s25
 
7.5%
r24
 
7.2%
h19
 
5.7%
g18
 
5.4%
m12
 
3.6%
Other values (9)63
18.9%
Uppercase Letter
ValueCountFrequency (%)
A26
33.3%
S9
 
11.5%
K9
 
11.5%
N8
 
10.3%
E7
 
9.0%
Y7
 
9.0%
H5
 
6.4%
O2
 
2.6%
L2
 
2.6%
B2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
/33
100.0%
Connector Punctuation
ValueCountFrequency (%)
_12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin412
90.2%
Common45
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a54
13.1%
o34
 
8.3%
i34
 
8.3%
A26
 
6.3%
e26
 
6.3%
n25
 
6.1%
s25
 
6.1%
r24
 
5.8%
h19
 
4.6%
g18
 
4.4%
Other values (20)127
30.8%
Common
ValueCountFrequency (%)
/33
73.3%
_12
 
26.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII457
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a54
 
11.8%
o34
 
7.4%
i34
 
7.4%
/33
 
7.2%
A26
 
5.7%
e26
 
5.7%
n25
 
5.5%
s25
 
5.5%
r24
 
5.3%
h19
 
4.2%
Other values (22)157
34.4%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)31.6%
Missing48
Missing (%)55.8%
Memory size816.0 B
https://www.youtube.com
16 
https://www.iq.com/
https://v.qq.com/
https://www.netflix.com/
https://www.channel4.com/
Other values (7)

Length

Max length30
Median length26
Mean length22.42105263
Min length17

Characters and Unicode

Total characters852
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)18.4%

Sample

1st rowhttps://www.vlive.tv/home
2nd rowhttps://v.qq.com/
3rd rowhttps://v.qq.com/
4th rowhttps://www.youtube.com
5th rowhttps://www.youtube.com

Common Values

ValueCountFrequency (%)
https://www.youtube.com16
 
18.6%
https://www.iq.com/5
 
5.8%
https://v.qq.com/4
 
4.7%
https://www.netflix.com/4
 
4.7%
https://www.channel4.com/2
 
2.3%
https://www.vlive.tv/home1
 
1.2%
https://wetv.vip/1
 
1.2%
https://www.discoveryplus.com/1
 
1.2%
http://www.wowpresentsplus.com1
 
1.2%
https://www.primevideo.com1
 
1.2%
Other values (2)2
 
2.3%
(Missing)48
55.8%

Length

2022-09-05T21:39:10.002027image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com16
42.1%
https://www.iq.com5
 
13.2%
https://v.qq.com4
 
10.5%
https://www.netflix.com4
 
10.5%
https://www.channel4.com2
 
5.3%
https://www.vlive.tv/home1
 
2.6%
https://wetv.vip1
 
2.6%
https://www.discoveryplus.com1
 
2.6%
http://www.wowpresentsplus.com1
 
2.6%
https://www.primevideo.com1
 
2.6%
Other values (2)2
 
5.3%

Most occurring characters

ValueCountFrequency (%)
t101
11.9%
w99
11.6%
/96
11.3%
.75
 
8.8%
o57
 
6.7%
p44
 
5.2%
s42
 
4.9%
h41
 
4.8%
c41
 
4.8%
:38
 
4.5%
Other values (17)218
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter641
75.2%
Other Punctuation209
 
24.5%
Decimal Number2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t101
15.8%
w99
15.4%
o57
8.9%
p44
 
6.9%
s42
 
6.6%
h41
 
6.4%
c41
 
6.4%
m38
 
5.9%
u34
 
5.3%
e32
 
5.0%
Other values (13)112
17.5%
Other Punctuation
ValueCountFrequency (%)
/96
45.9%
.75
35.9%
:38
 
18.2%
Decimal Number
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin641
75.2%
Common211
 
24.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t101
15.8%
w99
15.4%
o57
8.9%
p44
 
6.9%
s42
 
6.6%
h41
 
6.4%
c41
 
6.4%
m38
 
5.9%
u34
 
5.3%
e32
 
5.0%
Other values (13)112
17.5%
Common
ValueCountFrequency (%)
/96
45.5%
.75
35.5%
:38
 
18.0%
42
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t101
11.9%
w99
11.6%
/96
11.3%
.75
 
8.8%
o57
 
6.7%
p44
 
5.2%
s42
 
4.9%
h41
 
4.8%
c41
 
4.8%
:38
 
4.5%
Other values (17)218
25.6%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing86
Missing (%)100.0%
Memory size816.0 B

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing83
Missing (%)96.5%
Memory size816.0 B
30282.0
19056.0
6659.0

Length

Max length7
Median length7
Mean length6.666666667
Min length6

Characters and Unicode

Total characters20
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row30282.0
2nd row19056.0
3rd row6659.0

Common Values

ValueCountFrequency (%)
30282.01
 
1.2%
19056.01
 
1.2%
6659.01
 
1.2%
(Missing)83
96.5%

Length

2022-09-05T21:39:10.110420image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:10.222996image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
30282.01
33.3%
19056.01
33.3%
6659.01
33.3%

Most occurring characters

ValueCountFrequency (%)
05
25.0%
.3
15.0%
63
15.0%
22
 
10.0%
92
 
10.0%
52
 
10.0%
31
 
5.0%
81
 
5.0%
11
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number17
85.0%
Other Punctuation3
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
05
29.4%
63
17.6%
22
 
11.8%
92
 
11.8%
52
 
11.8%
31
 
5.9%
81
 
5.9%
11
 
5.9%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
05
25.0%
.3
15.0%
63
15.0%
22
 
10.0%
92
 
10.0%
52
 
10.0%
31
 
5.0%
81
 
5.0%
11
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
05
25.0%
.3
15.0%
63
15.0%
22
 
10.0%
92
 
10.0%
52
 
10.0%
31
 
5.0%
81
 
5.0%
11
 
5.0%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct44
Distinct (%)64.7%
Missing18
Missing (%)20.9%
Infinite0
Infinite (%)0.0%
Mean348644.5735
Minimum73246
Maximum408956
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:10.318113image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum73246
5-th percentile118523
Q1336364.5
median391989
Q3393098
95-th percentile393838.15
Maximum408956
Range335710
Interquartile range (IQR)56733.5

Descriptive statistics

Standard deviation82879.2761
Coefficient of variation (CV)0.2377185317
Kurtosis4.578501664
Mean348644.5735
Median Absolute Deviation (MAD)1475
Skewness-2.262499144
Sum23707831
Variance6868974407
MonotonicityNot monotonic
2022-09-05T21:39:10.459097image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
3934548
 
9.3%
3930986
 
7.0%
3919895
 
5.8%
3926544
 
4.7%
2787932
 
2.3%
4089562
 
2.3%
3923552
 
2.3%
3922142
 
2.3%
3923622
 
2.3%
2651931
 
1.2%
Other values (34)34
39.5%
(Missing)18
20.9%
ValueCountFrequency (%)
732461
1.2%
767791
1.2%
788961
1.2%
1042711
1.2%
1449911
1.2%
2479561
1.2%
2608291
1.2%
2644581
1.2%
2651931
1.2%
2787932
2.3%
ValueCountFrequency (%)
4089562
 
2.3%
4017901
 
1.2%
3940451
 
1.2%
3934548
9.3%
3930986
7.0%
3926821
 
1.2%
3926544
4.7%
3926491
 
1.2%
3923991
 
1.2%
3923622
 
2.3%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct25
Distinct (%)59.5%
Missing44
Missing (%)51.2%
Memory size816.0 B
tt13442632
tt13598530
tt13540900
tt1714810
 
2
tt13539710
 
2
Other values (20)
20 

Length

Max length10
Median length10
Mean length9.69047619
Min length9

Characters and Unicode

Total characters407
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)47.6%

Sample

1st rowtt12923874
2nd rowtt11492320
3rd rowtt13449378
4th rowtt0401747
5th rowtt1714810

Common Values

ValueCountFrequency (%)
tt134426328
 
9.3%
tt135985306
 
7.0%
tt135409004
 
4.7%
tt17148102
 
2.3%
tt135397102
 
2.3%
tt114923201
 
1.2%
tt124579461
 
1.2%
tt01851031
 
1.2%
tt112191641
 
1.2%
tt00965971
 
1.2%
Other values (15)15
 
17.4%
(Missing)44
51.2%

Length

2022-09-05T21:39:10.572107image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt134426328
19.0%
tt135985306
 
14.3%
tt135409004
 
9.5%
tt17148102
 
4.8%
tt135397102
 
4.8%
tt124856361
 
2.4%
tt04017471
 
2.4%
tt03375341
 
2.4%
tt40870321
 
2.4%
tt37676661
 
2.4%
Other values (15)15
35.7%

Most occurring characters

ValueCountFrequency (%)
t84
20.6%
354
13.3%
149
12.0%
439
9.6%
034
8.4%
230
 
7.4%
529
 
7.1%
824
 
5.9%
623
 
5.7%
923
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number323
79.4%
Lowercase Letter84
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
354
16.7%
149
15.2%
439
12.1%
034
10.5%
230
9.3%
529
9.0%
824
7.4%
623
7.1%
923
7.1%
718
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
t84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common323
79.4%
Latin84
 
20.6%

Most frequent character per script

Common
ValueCountFrequency (%)
354
16.7%
149
15.2%
439
12.1%
034
10.5%
230
9.3%
529
9.0%
824
7.4%
623
7.1%
923
7.1%
718
 
5.6%
Latin
ValueCountFrequency (%)
t84
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t84
20.6%
354
13.3%
149
12.0%
439
9.6%
034
8.4%
230
 
7.4%
529
 
7.1%
824
 
5.9%
623
 
5.7%
923
 
5.7%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct55
Distinct (%)72.4%
Missing10
Missing (%)11.6%
Memory size816.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/291/728420.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/288/721823.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/287/717779.jpg
 
4
https://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg
 
2
Other values (50)
54 

Length

Max length72
Median length71
Mean length70.94736842
Min length69

Characters and Unicode

Total characters5392
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)60.5%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/394/985825.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/276/690795.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/291/728420.jpg8
 
9.3%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721823.jpg6
 
7.0%
https://static.tvmaze.com/uploads/images/medium_portrait/287/717779.jpg4
 
4.7%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718116.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/medium_portrait/65/164161.jpg1
 
1.2%
Other values (45)45
52.3%
(Missing)10
 
11.6%

Length

2022-09-05T21:39:10.670251image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/291/728420.jpg8
 
10.5%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721823.jpg6
 
7.9%
https://static.tvmaze.com/uploads/images/medium_portrait/287/717779.jpg4
 
5.3%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718116.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/282/706333.jpg1
 
1.3%
Other values (45)45
59.2%

Most occurring characters

ValueCountFrequency (%)
t532
 
9.9%
/532
 
9.9%
m380
 
7.0%
a380
 
7.0%
p304
 
5.6%
s304
 
5.6%
i304
 
5.6%
.228
 
4.2%
o228
 
4.2%
e228
 
4.2%
Other values (22)1972
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3800
70.5%
Other Punctuation836
 
15.5%
Decimal Number680
 
12.6%
Connector Punctuation76
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t532
14.0%
m380
10.0%
a380
10.0%
p304
 
8.0%
s304
 
8.0%
i304
 
8.0%
o228
 
6.0%
e228
 
6.0%
u152
 
4.0%
r152
 
4.0%
Other values (8)836
22.0%
Decimal Number
ValueCountFrequency (%)
2107
15.7%
795
14.0%
191
13.4%
891
13.4%
056
8.2%
556
8.2%
453
7.8%
951
7.5%
346
6.8%
634
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/532
63.6%
.228
27.3%
:76
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3800
70.5%
Common1592
29.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t532
14.0%
m380
10.0%
a380
10.0%
p304
 
8.0%
s304
 
8.0%
i304
 
8.0%
o228
 
6.0%
e228
 
6.0%
u152
 
4.0%
r152
 
4.0%
Other values (8)836
22.0%
Common
ValueCountFrequency (%)
/532
33.4%
.228
14.3%
2107
 
6.7%
795
 
6.0%
191
 
5.7%
891
 
5.7%
_76
 
4.8%
:76
 
4.8%
056
 
3.5%
556
 
3.5%
Other values (4)184
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII5392
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t532
 
9.9%
/532
 
9.9%
m380
 
7.0%
a380
 
7.0%
p304
 
5.6%
s304
 
5.6%
i304
 
5.6%
.228
 
4.2%
o228
 
4.2%
e228
 
4.2%
Other values (22)1972
36.6%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct55
Distinct (%)72.4%
Missing10
Missing (%)11.6%
Memory size816.0 B
https://static.tvmaze.com/uploads/images/original_untouched/291/728420.jpg
https://static.tvmaze.com/uploads/images/original_untouched/288/721823.jpg
https://static.tvmaze.com/uploads/images/original_untouched/287/717779.jpg
 
4
https://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg
 
2
Other values (50)
54 

Length

Max length75
Median length74
Mean length73.94736842
Min length72

Characters and Unicode

Total characters5620
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)60.5%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/394/985825.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/276/690795.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/291/728420.jpg8
 
9.3%
https://static.tvmaze.com/uploads/images/original_untouched/288/721823.jpg6
 
7.0%
https://static.tvmaze.com/uploads/images/original_untouched/287/717779.jpg4
 
4.7%
https://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/287/718116.jpg2
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/65/164161.jpg1
 
1.2%
Other values (45)45
52.3%
(Missing)10
 
11.6%

Length

2022-09-05T21:39:10.789819image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/291/728420.jpg8
 
10.5%
https://static.tvmaze.com/uploads/images/original_untouched/288/721823.jpg6
 
7.9%
https://static.tvmaze.com/uploads/images/original_untouched/287/717779.jpg4
 
5.3%
https://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/287/718116.jpg2
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/282/706333.jpg1
 
1.3%
Other values (45)45
59.2%

Most occurring characters

ValueCountFrequency (%)
/532
 
9.5%
t456
 
8.1%
a380
 
6.8%
s304
 
5.4%
i304
 
5.4%
o304
 
5.4%
p228
 
4.1%
c228
 
4.1%
.228
 
4.1%
g228
 
4.1%
Other values (23)2428
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4028
71.7%
Other Punctuation836
 
14.9%
Decimal Number680
 
12.1%
Connector Punctuation76
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t456
 
11.3%
a380
 
9.4%
s304
 
7.5%
i304
 
7.5%
o304
 
7.5%
p228
 
5.7%
c228
 
5.7%
g228
 
5.7%
m228
 
5.7%
e228
 
5.7%
Other values (9)1140
28.3%
Decimal Number
ValueCountFrequency (%)
2107
15.7%
795
14.0%
191
13.4%
891
13.4%
056
8.2%
556
8.2%
453
7.8%
951
7.5%
346
6.8%
634
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/532
63.6%
.228
27.3%
:76
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4028
71.7%
Common1592
 
28.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t456
 
11.3%
a380
 
9.4%
s304
 
7.5%
i304
 
7.5%
o304
 
7.5%
p228
 
5.7%
c228
 
5.7%
g228
 
5.7%
m228
 
5.7%
e228
 
5.7%
Other values (9)1140
28.3%
Common
ValueCountFrequency (%)
/532
33.4%
.228
14.3%
2107
 
6.7%
795
 
6.0%
191
 
5.7%
891
 
5.7%
:76
 
4.8%
_76
 
4.8%
056
 
3.5%
556
 
3.5%
Other values (4)184
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII5620
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/532
 
9.5%
t456
 
8.1%
a380
 
6.8%
s304
 
5.4%
i304
 
5.4%
o304
 
5.4%
p228
 
4.1%
c228
 
4.1%
.228
 
4.1%
g228
 
4.1%
Other values (23)2428
43.2%

_embedded.show.summary
Categorical

HIGH CORRELATION
MISSING

Distinct50
Distinct (%)70.4%
Missing15
Missing (%)17.4%
Memory size816.0 B
<p>When an Arab celebrity has a problem, fixer Tony Tabet is the solution. Now he wants out to reconnect with his son, and with one month left on the job.</p>
<p>A race against time and the elements using high tech that could go fatally wrong - this is Light Speed. Join Derek Muller of Veritasium to meet the minds (and understand the physics!) behind the world's most advanced solar vehicles as they race 2,000 miles across the Australian Outback.</p>
<p><b>Room 2806: The Accusation</b> traces the 2011 sexual assault case involving French politician Dominique Strauss, who was then at the height of his career. On 14 May 2011, Nafissatou Diallo, a 32-year-old maid at the Sofitel New York Hotel, alleged that Strauss-Kahn had sexually assaulted her after she entered his suite. Hear the full story from people who were involved in the alleged incident and subsequent trial.</p>
 
4
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>
 
2
<p>From bargain to deluxe, Poundland are on a mission to transform their reputation and go upmarket, from investing millions on opening new stores and undergoing refits to launching new product ranges.</p>
 
2
Other values (45)
49 

Length

Max length877
Median length437
Mean length307.943662
Min length58

Characters and Unicode

Total characters21864
Distinct characters99
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)57.7%

Sample

1st row<p>Initially a series of behind-the-scenes vlogs, <b>Going Seventeen</b> has taken a more structured route since mid-2019 and is now a reality-variety show with themed episodes. Every week, the members of Seventeen play games or participate in a variety of activities for everyone's delight and entertainment. Season 2021's keyword is "Watch What You Say", meaning that anything the members say can and will be turned into content...</p>
2nd row<p>One day in 20XX, the alien pig prince who planned to take a human body as his home arrived on Earth, but unexpectedly discovered that the human being he wanted to live in had not yet been born! The pig prince, who has nowhere to settle down, got to know Saiji and Rubi. The three pulled various funny pranks on humans, causing humans to have baldness, bad breath, headaches, emotional crisis and other problems.</p>
3rd row<p>The master of Ye Xing Yun will ascend to heaven, leaving behind the great strength of the Tian Yuan Sect, and Ye Xing Yun making the new Sovereign of the Tian Yuan Sect, and at the request of his master, seek revenge by entering into a small family while waiting to perform revenge. Ye Xing Yun embarks on an extremely dangerous road, but with his strategy, and with the help of the masters of the Tian Yuan Sect, his long-term strategy of confrontation with the huge Zhou dynasty.</p>
4th row<p>Ten thousand years ago, Muyun's fairy King was secretly accounted for by holding a Zhuxian figure, and after a long sleep, he awakened in the famous "Muyun waste" of the southern Yun Empire in the Land of Heaven. When Muyun first woke up, he was deliberately bothered by the student Miaoxianyu. Muyun easily completed the Miaoxianyu trap, and he gave more and more alchemy skills by analogy, so the Alchemy masters outside the door could not ask for appreciation. Endless back home, Mu Yun learns that he is about to marry Nona Qin Qin Mengyao. Qin Mengyao was cold and toxic, but could not live until he was 20 years old. The marriage was only for the sake of pastoralists and family of Qin. However, under Mu Linchen's enticement, Mu Yun approves the family's issue on the condition of alchemy.</p><p><br /> </p>
5th row<p>The parents get divorced and Jo has to move to a new place. One day, Nordstjerna goes out, and Jo discovers that a girl with magical powers lives in the attic.</p>

Common Values

ValueCountFrequency (%)
<p>When an Arab celebrity has a problem, fixer Tony Tabet is the solution. Now he wants out to reconnect with his son, and with one month left on the job.</p>8
 
9.3%
<p>A race against time and the elements using high tech that could go fatally wrong - this is Light Speed. Join Derek Muller of Veritasium to meet the minds (and understand the physics!) behind the world's most advanced solar vehicles as they race 2,000 miles across the Australian Outback.</p>6
 
7.0%
<p><b>Room 2806: The Accusation</b> traces the 2011 sexual assault case involving French politician Dominique Strauss, who was then at the height of his career. On 14 May 2011, Nafissatou Diallo, a 32-year-old maid at the Sofitel New York Hotel, alleged that Strauss-Kahn had sexually assaulted her after she entered his suite. Hear the full story from people who were involved in the alleged incident and subsequent trial.</p>4
 
4.7%
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>2
 
2.3%
<p>From bargain to deluxe, Poundland are on a mission to transform their reputation and go upmarket, from investing millions on opening new stores and undergoing refits to launching new product ranges.</p>2
 
2.3%
<p>89 prisoners escaped from Pārlielupe Prison, tens of thousands of people were involved in their search, and mass arrests continued for ten years. Dramas of mutual relations, a massive and enigmatic escape is organized, in parallel with the flourishing of the love of the main character and the daughter of the head of the prison and the hopes for a new, beautiful life.</p>2
 
2.3%
<p>A story that follows people whose lives are entangled due to a complicated case. While investigating a drug cartel as an undercover cop, Yan Jin falls in love with the beautiful coffee shop owner Ji Xiao'ou.</p>2
 
2.3%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
2.3%
<p>Merchant Jiang Shuo and his odd specialist companion Qin Yi Heng purchase frequented houses to exchange them. In any case, alarming things start to occur and each spooky house is by all accounts part of a major riddle. Jiang Shuo, Yi Heng, and police officer Yuan Mu Qing attempt to understand the riddle.</p>2
 
2.3%
<p><b>SciShow</b> explores the unexpected. Seven days a week, Hank Green, Michael Aranda, and Olivia Gordon delve into the scientific subjects that defy our expectations and make us even more curious!</p><p>Schedule:</p><p>Sundays — Learn about the amazing topics we can't quite make a stand-alone show about in SciShow List Show!</p><p>Mondays — Tune in for a short Dose about our weird world.</p><p>Tuesdays — Find answers to our most asked Quick Questions.</p><p>Wednesdays — Hank or Michael dives deep into a long-form Infusion episode, or an unscripted talk show or quiz show with a guest!</p><p>Thursday — Another new dose about the wonders of the world.</p><p>Fridays — Learn the latest in science News.</p><p>Saturdays — Get your quick questions answered!</p>1
 
1.2%
Other values (40)40
46.5%
(Missing)15
 
17.4%

Length

2022-09-05T21:39:10.915654image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the221
 
6.0%
and124
 
3.4%
to98
 
2.7%
of92
 
2.5%
a86
 
2.3%
in64
 
1.7%
with48
 
1.3%
is40
 
1.1%
on35
 
1.0%
his31
 
0.8%
Other values (1272)2821
77.1%

Most occurring characters

ValueCountFrequency (%)
3583
16.4%
e2005
 
9.2%
t1422
 
6.5%
a1354
 
6.2%
n1260
 
5.8%
o1251
 
5.7%
i1151
 
5.3%
s1097
 
5.0%
r988
 
4.5%
h895
 
4.1%
Other values (89)6858
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter16337
74.7%
Space Separator3589
 
16.4%
Uppercase Letter741
 
3.4%
Other Punctuation586
 
2.7%
Math Symbol382
 
1.7%
Decimal Number148
 
0.7%
Dash Punctuation41
 
0.2%
Close Punctuation13
 
0.1%
Open Punctuation13
 
0.1%
Other Letter13
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2005
12.3%
t1422
 
8.7%
a1354
 
8.3%
n1260
 
7.7%
o1251
 
7.7%
i1151
 
7.0%
s1097
 
6.7%
r988
 
6.0%
h895
 
5.5%
l663
 
4.1%
Other values (21)4251
26.0%
Uppercase Letter
ValueCountFrequency (%)
T70
 
9.4%
S64
 
8.6%
A61
 
8.2%
Y51
 
6.9%
W48
 
6.5%
M44
 
5.9%
D39
 
5.3%
R34
 
4.6%
L32
 
4.3%
J28
 
3.8%
Other values (16)270
36.4%
Other Letter
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%
Other Punctuation
ValueCountFrequency (%)
,223
38.1%
.174
29.7%
/97
16.6%
'44
 
7.5%
"22
 
3.8%
!13
 
2.2%
:8
 
1.4%
?3
 
0.5%
&1
 
0.2%
;1
 
0.2%
Decimal Number
ValueCountFrequency (%)
042
28.4%
234
23.0%
133
22.3%
89
 
6.1%
98
 
5.4%
38
 
5.4%
66
 
4.1%
44
 
2.7%
72
 
1.4%
52
 
1.4%
Space Separator
ValueCountFrequency (%)
3583
99.8%
 6
 
0.2%
Math Symbol
ValueCountFrequency (%)
<191
50.0%
>191
50.0%
Dash Punctuation
ValueCountFrequency (%)
-33
80.5%
8
 
19.5%
Close Punctuation
ValueCountFrequency (%)
)13
100.0%
Open Punctuation
ValueCountFrequency (%)
(13
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin17078
78.1%
Common4773
 
21.8%
Han13
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2005
11.7%
t1422
 
8.3%
a1354
 
7.9%
n1260
 
7.4%
o1251
 
7.3%
i1151
 
6.7%
s1097
 
6.4%
r988
 
5.8%
h895
 
5.2%
l663
 
3.9%
Other values (47)4992
29.2%
Common
ValueCountFrequency (%)
3583
75.1%
,223
 
4.7%
<191
 
4.0%
>191
 
4.0%
.174
 
3.6%
/97
 
2.0%
'44
 
0.9%
042
 
0.9%
234
 
0.7%
133
 
0.7%
Other values (19)161
 
3.4%
Han
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII21831
99.8%
CJK13
 
0.1%
None12
 
0.1%
Punctuation8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3583
16.4%
e2005
 
9.2%
t1422
 
6.5%
a1354
 
6.2%
n1260
 
5.8%
o1251
 
5.7%
i1151
 
5.3%
s1097
 
5.0%
r988
 
4.5%
h895
 
4.1%
Other values (69)6825
31.3%
Punctuation
ValueCountFrequency (%)
8
100.0%
None
ValueCountFrequency (%)
 6
50.0%
ā2
 
16.7%
é1
 
8.3%
ı1
 
8.3%
ç1
 
8.3%
å1
 
8.3%
CJK
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct59
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1634329919
Minimum1602172227
Maximum1662346277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:11.051075image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1602172227
5-th percentile1608999255
Q11614622943
median1639409829
Q31651553385
95-th percentile1661565111
Maximum1662346277
Range60174050
Interquartile range (IQR)36930442.25

Descriptive statistics

Standard deviation19870463.72
Coefficient of variation (CV)0.01215817167
Kurtosis-1.608363299
Mean1634329919
Median Absolute Deviation (MAD)21427265.5
Skewness-0.03517179291
Sum1.40552373 × 1011
Variance3.948353284 × 1014
MonotonicityNot monotonic
2022-09-05T21:39:11.179434image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16146229438
 
9.3%
16089992556
 
7.0%
16151929545
 
5.8%
16158543454
 
4.7%
16404355312
 
2.3%
16481900582
 
2.3%
16073820732
 
2.3%
16362363312
 
2.3%
16196365812
 
2.3%
16090607262
 
2.3%
Other values (49)51
59.3%
ValueCountFrequency (%)
16021722271
 
1.2%
16073820732
 
2.3%
16089992556
7.0%
16090607262
 
2.3%
16095351412
 
2.3%
16114368421
 
1.2%
16130883481
 
1.2%
16133564461
 
1.2%
16146229438
9.3%
16151929545
5.8%
ValueCountFrequency (%)
16623462771
1.2%
16621306411
1.2%
16620480541
1.2%
16616900451
1.2%
16616322671
1.2%
16613636441
1.2%
16613587701
1.2%
16609226001
1.2%
16609157101
1.2%
16607584791
1.2%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct59
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size816.0 B
https://api.tvmaze.com/shows/52730
https://api.tvmaze.com/shows/52422
 
6
https://api.tvmaze.com/shows/51954
 
5
https://api.tvmaze.com/shows/52272
 
4
https://api.tvmaze.com/shows/52181
 
2
Other values (54)
61 

Length

Max length34
Median length34
Mean length33.93023256
Min length32

Characters and Unicode

Total characters2918
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)54.7%

Sample

1st rowhttps://api.tvmaze.com/shows/52181
2nd rowhttps://api.tvmaze.com/shows/52181
3rd rowhttps://api.tvmaze.com/shows/52198
4th rowhttps://api.tvmaze.com/shows/56655
5th rowhttps://api.tvmaze.com/shows/50916

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/527308
 
9.3%
https://api.tvmaze.com/shows/524226
 
7.0%
https://api.tvmaze.com/shows/519545
 
5.8%
https://api.tvmaze.com/shows/522724
 
4.7%
https://api.tvmaze.com/shows/521812
 
2.3%
https://api.tvmaze.com/shows/152502
 
2.3%
https://api.tvmaze.com/shows/522872
 
2.3%
https://api.tvmaze.com/shows/588212
 
2.3%
https://api.tvmaze.com/shows/549962
 
2.3%
https://api.tvmaze.com/shows/521592
 
2.3%
Other values (49)51
59.3%

Length

2022-09-05T21:39:11.293754image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/527308
 
9.3%
https://api.tvmaze.com/shows/524226
 
7.0%
https://api.tvmaze.com/shows/519545
 
5.8%
https://api.tvmaze.com/shows/522724
 
4.7%
https://api.tvmaze.com/shows/549962
 
2.3%
https://api.tvmaze.com/shows/521082
 
2.3%
https://api.tvmaze.com/shows/521592
 
2.3%
https://api.tvmaze.com/shows/521042
 
2.3%
https://api.tvmaze.com/shows/588212
 
2.3%
https://api.tvmaze.com/shows/522872
 
2.3%
Other values (49)51
59.3%

Most occurring characters

ValueCountFrequency (%)
/344
 
11.8%
s258
 
8.8%
t258
 
8.8%
h172
 
5.9%
p172
 
5.9%
a172
 
5.9%
.172
 
5.9%
o172
 
5.9%
m172
 
5.9%
587
 
3.0%
Other values (16)939
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1892
64.8%
Other Punctuation602
 
20.6%
Decimal Number424
 
14.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s258
13.6%
t258
13.6%
h172
9.1%
p172
9.1%
a172
9.1%
o172
9.1%
m172
9.1%
e86
 
4.5%
w86
 
4.5%
c86
 
4.5%
Other values (3)258
13.6%
Decimal Number
ValueCountFrequency (%)
587
20.5%
273
17.2%
144
10.4%
039
9.2%
438
9.0%
732
 
7.5%
932
 
7.5%
327
 
6.4%
826
 
6.1%
626
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/344
57.1%
.172
28.6%
:86
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1892
64.8%
Common1026
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/344
33.5%
.172
16.8%
587
 
8.5%
:86
 
8.4%
273
 
7.1%
144
 
4.3%
039
 
3.8%
438
 
3.7%
732
 
3.1%
932
 
3.1%
Other values (3)79
 
7.7%
Latin
ValueCountFrequency (%)
s258
13.6%
t258
13.6%
h172
9.1%
p172
9.1%
a172
9.1%
o172
9.1%
m172
9.1%
e86
 
4.5%
w86
 
4.5%
c86
 
4.5%
Other values (3)258
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2918
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/344
 
11.8%
s258
 
8.8%
t258
 
8.8%
h172
 
5.9%
p172
 
5.9%
a172
 
5.9%
.172
 
5.9%
o172
 
5.9%
m172
 
5.9%
587
 
3.0%
Other values (16)939
32.2%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct59
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size816.0 B
https://api.tvmaze.com/episodes/1996355
https://api.tvmaze.com/episodes/1985406
 
6
https://api.tvmaze.com/episodes/1971211
 
5
https://api.tvmaze.com/episodes/1981559
 
4
https://api.tvmaze.com/episodes/1982412
 
2
Other values (54)
61 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3354
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)54.7%

Sample

1st rowhttps://api.tvmaze.com/episodes/1982412
2nd rowhttps://api.tvmaze.com/episodes/1982412
3rd rowhttps://api.tvmaze.com/episodes/1986873
4th rowhttps://api.tvmaze.com/episodes/2383576
5th rowhttps://api.tvmaze.com/episodes/1945592

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19963558
 
9.3%
https://api.tvmaze.com/episodes/19854066
 
7.0%
https://api.tvmaze.com/episodes/19712115
 
5.8%
https://api.tvmaze.com/episodes/19815594
 
4.7%
https://api.tvmaze.com/episodes/19824122
 
2.3%
https://api.tvmaze.com/episodes/23012762
 
2.3%
https://api.tvmaze.com/episodes/19816152
 
2.3%
https://api.tvmaze.com/episodes/22111472
 
2.3%
https://api.tvmaze.com/episodes/20790092
 
2.3%
https://api.tvmaze.com/episodes/19776512
 
2.3%
Other values (49)51
59.3%

Length

2022-09-05T21:39:11.381687image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19963558
 
9.3%
https://api.tvmaze.com/episodes/19854066
 
7.0%
https://api.tvmaze.com/episodes/19712115
 
5.8%
https://api.tvmaze.com/episodes/19815594
 
4.7%
https://api.tvmaze.com/episodes/20790092
 
2.3%
https://api.tvmaze.com/episodes/19762022
 
2.3%
https://api.tvmaze.com/episodes/19776512
 
2.3%
https://api.tvmaze.com/episodes/19760542
 
2.3%
https://api.tvmaze.com/episodes/22111472
 
2.3%
https://api.tvmaze.com/episodes/19816152
 
2.3%
Other values (49)51
59.3%

Most occurring characters

ValueCountFrequency (%)
/344
 
10.3%
t258
 
7.7%
p258
 
7.7%
s258
 
7.7%
e258
 
7.7%
a172
 
5.1%
i172
 
5.1%
.172
 
5.1%
m172
 
5.1%
o172
 
5.1%
Other values (16)1118
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2150
64.1%
Other Punctuation602
 
17.9%
Decimal Number602
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t258
12.0%
p258
12.0%
s258
12.0%
e258
12.0%
a172
8.0%
i172
8.0%
m172
8.0%
o172
8.0%
d86
 
4.0%
h86
 
4.0%
Other values (3)258
12.0%
Decimal Number
ValueCountFrequency (%)
297
16.1%
196
15.9%
979
13.1%
559
9.8%
354
9.0%
054
9.0%
747
7.8%
639
6.5%
439
6.5%
838
 
6.3%
Other Punctuation
ValueCountFrequency (%)
/344
57.1%
.172
28.6%
:86
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2150
64.1%
Common1204
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/344
28.6%
.172
14.3%
297
 
8.1%
196
 
8.0%
:86
 
7.1%
979
 
6.6%
559
 
4.9%
354
 
4.5%
054
 
4.5%
747
 
3.9%
Other values (3)116
 
9.6%
Latin
ValueCountFrequency (%)
t258
12.0%
p258
12.0%
s258
12.0%
e258
12.0%
a172
8.0%
i172
8.0%
m172
8.0%
o172
8.0%
d86
 
4.0%
h86
 
4.0%
Other values (3)258
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/344
 
10.3%
t258
 
7.7%
p258
 
7.7%
s258
 
7.7%
e258
 
7.7%
a172
 
5.1%
i172
 
5.1%
.172
 
5.1%
m172
 
5.1%
o172
 
5.1%
Other values (16)1118
33.3%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct7
Distinct (%)100.0%
Missing79
Missing (%)91.9%
Memory size816.0 B
https://api.tvmaze.com/episodes/2383577
https://api.tvmaze.com/episodes/2381297
https://api.tvmaze.com/episodes/2375175
https://api.tvmaze.com/episodes/2330185
https://api.tvmaze.com/episodes/2350916
Other values (2)

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters273
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2383577
2nd rowhttps://api.tvmaze.com/episodes/2381297
3rd rowhttps://api.tvmaze.com/episodes/2375175
4th rowhttps://api.tvmaze.com/episodes/2330185
5th rowhttps://api.tvmaze.com/episodes/2350916

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23835771
 
1.2%
https://api.tvmaze.com/episodes/23812971
 
1.2%
https://api.tvmaze.com/episodes/23751751
 
1.2%
https://api.tvmaze.com/episodes/23301851
 
1.2%
https://api.tvmaze.com/episodes/23509161
 
1.2%
https://api.tvmaze.com/episodes/23797031
 
1.2%
https://api.tvmaze.com/episodes/23488431
 
1.2%
(Missing)79
91.9%

Length

2022-09-05T21:39:11.463606image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:11.592681image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23835771
14.3%
https://api.tvmaze.com/episodes/23812971
14.3%
https://api.tvmaze.com/episodes/23751751
14.3%
https://api.tvmaze.com/episodes/23301851
14.3%
https://api.tvmaze.com/episodes/23509161
14.3%
https://api.tvmaze.com/episodes/23797031
14.3%
https://api.tvmaze.com/episodes/23488431
14.3%

Most occurring characters

ValueCountFrequency (%)
/28
 
10.3%
p21
 
7.7%
s21
 
7.7%
e21
 
7.7%
t21
 
7.7%
a14
 
5.1%
i14
 
5.1%
.14
 
5.1%
m14
 
5.1%
o14
 
5.1%
Other values (16)91
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter175
64.1%
Other Punctuation49
 
17.9%
Decimal Number49
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p21
12.0%
s21
12.0%
e21
12.0%
t21
12.0%
a14
8.0%
i14
8.0%
m14
8.0%
o14
8.0%
h7
 
4.0%
d7
 
4.0%
Other values (3)21
12.0%
Decimal Number
ValueCountFrequency (%)
311
22.4%
28
16.3%
77
14.3%
85
10.2%
55
10.2%
14
 
8.2%
93
 
6.1%
03
 
6.1%
42
 
4.1%
61
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/28
57.1%
.14
28.6%
:7
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin175
64.1%
Common98
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/28
28.6%
.14
14.3%
311
 
11.2%
28
 
8.2%
77
 
7.1%
:7
 
7.1%
85
 
5.1%
55
 
5.1%
14
 
4.1%
93
 
3.1%
Other values (3)6
 
6.1%
Latin
ValueCountFrequency (%)
p21
12.0%
s21
12.0%
e21
12.0%
t21
12.0%
a14
8.0%
i14
8.0%
m14
8.0%
o14
8.0%
h7
 
4.0%
d7
 
4.0%
Other values (3)21
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII273
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/28
 
10.3%
p21
 
7.7%
s21
 
7.7%
e21
 
7.7%
t21
 
7.7%
a14
 
5.1%
i14
 
5.1%
.14
 
5.1%
m14
 
5.1%
o14
 
5.1%
Other values (16)91
33.3%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct16
Distinct (%)100.0%
Missing70
Missing (%)81.4%
Memory size816.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/287/718017.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/293/734732.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/343/857757.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/287/718042.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/417/1044136.jpg
 
1
Other values (11)
11 

Length

Max length73
Median length72
Mean length72.1875
Min length72

Characters and Unicode

Total characters1155
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726341.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/718158.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/718654.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/418/1047205.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/718103.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/287/718017.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/293/734732.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/343/857757.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718042.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/417/1044136.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718019.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718018.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718016.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726341.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718194.jpg1
 
1.2%
Other values (6)6
 
7.0%
(Missing)70
81.4%

Length

2022-09-05T21:39:11.704603image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/287/718017.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/293/734732.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/343/857757.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718042.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/417/1044136.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718019.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718018.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718016.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726341.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718194.jpg1
 
6.2%
Other values (6)6
37.5%

Most occurring characters

ValueCountFrequency (%)
/112
 
9.7%
a96
 
8.3%
t80
 
6.9%
s80
 
6.9%
m80
 
6.9%
p64
 
5.5%
e64
 
5.5%
i48
 
4.2%
c48
 
4.2%
.48
 
4.2%
Other values (22)435
37.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter816
70.6%
Other Punctuation176
 
15.2%
Decimal Number147
 
12.7%
Connector Punctuation16
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a96
11.8%
t80
9.8%
s80
9.8%
m80
9.8%
p64
 
7.8%
e64
 
7.8%
i48
 
5.9%
c48
 
5.9%
d48
 
5.9%
l32
 
3.9%
Other values (8)176
21.6%
Decimal Number
ValueCountFrequency (%)
729
19.7%
125
17.0%
824
16.3%
219
12.9%
013
8.8%
412
8.2%
310
 
6.8%
66
 
4.1%
55
 
3.4%
94
 
2.7%
Other Punctuation
ValueCountFrequency (%)
/112
63.6%
.48
27.3%
:16
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin816
70.6%
Common339
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a96
11.8%
t80
9.8%
s80
9.8%
m80
9.8%
p64
 
7.8%
e64
 
7.8%
i48
 
5.9%
c48
 
5.9%
d48
 
5.9%
l32
 
3.9%
Other values (8)176
21.6%
Common
ValueCountFrequency (%)
/112
33.0%
.48
14.2%
729
 
8.6%
125
 
7.4%
824
 
7.1%
219
 
5.6%
_16
 
4.7%
:16
 
4.7%
013
 
3.8%
412
 
3.5%
Other values (4)25
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1155
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/112
 
9.7%
a96
 
8.3%
t80
 
6.9%
s80
 
6.9%
m80
 
6.9%
p64
 
5.5%
e64
 
5.5%
i48
 
4.2%
c48
 
4.2%
.48
 
4.2%
Other values (22)435
37.7%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct16
Distinct (%)100.0%
Missing70
Missing (%)81.4%
Memory size816.0 B
https://static.tvmaze.com/uploads/images/original_untouched/287/718017.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/293/734732.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/343/857757.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/287/718042.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/417/1044136.jpg
 
1
Other values (11)
11 

Length

Max length75
Median length74
Mean length74.1875
Min length74

Characters and Unicode

Total characters1187
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726341.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/718158.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/718654.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/418/1047205.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/718103.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/287/718017.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/293/734732.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/343/857757.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/718042.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/417/1044136.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/718019.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/718018.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/718016.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/726341.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/718194.jpg1
 
1.2%
Other values (6)6
 
7.0%
(Missing)70
81.4%

Length

2022-09-05T21:39:11.798647image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/287/718017.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/293/734732.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/343/857757.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/718042.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/417/1044136.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/718019.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/718018.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/718016.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/290/726341.jpg1
 
6.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/718194.jpg1
 
6.2%
Other values (6)6
37.5%

Most occurring characters

ValueCountFrequency (%)
/112
 
9.4%
t96
 
8.1%
a80
 
6.7%
s64
 
5.4%
i64
 
5.4%
o64
 
5.4%
p48
 
4.0%
c48
 
4.0%
.48
 
4.0%
g48
 
4.0%
Other values (23)515
43.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter848
71.4%
Other Punctuation176
 
14.8%
Decimal Number147
 
12.4%
Connector Punctuation16
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t96
 
11.3%
a80
 
9.4%
s64
 
7.5%
i64
 
7.5%
o64
 
7.5%
p48
 
5.7%
c48
 
5.7%
g48
 
5.7%
m48
 
5.7%
e48
 
5.7%
Other values (9)240
28.3%
Decimal Number
ValueCountFrequency (%)
729
19.7%
125
17.0%
824
16.3%
219
12.9%
013
8.8%
412
8.2%
310
 
6.8%
66
 
4.1%
55
 
3.4%
94
 
2.7%
Other Punctuation
ValueCountFrequency (%)
/112
63.6%
.48
27.3%
:16
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin848
71.4%
Common339
 
28.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t96
 
11.3%
a80
 
9.4%
s64
 
7.5%
i64
 
7.5%
o64
 
7.5%
p48
 
5.7%
c48
 
5.7%
g48
 
5.7%
m48
 
5.7%
e48
 
5.7%
Other values (9)240
28.3%
Common
ValueCountFrequency (%)
/112
33.0%
.48
14.2%
729
 
8.6%
125
 
7.4%
824
 
7.1%
219
 
5.6%
:16
 
4.7%
_16
 
4.7%
013
 
3.8%
412
 
3.5%
Other values (4)25
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1187
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/112
 
9.4%
t96
 
8.1%
a80
 
6.7%
s64
 
5.4%
i64
 
5.4%
o64
 
5.4%
p48
 
4.0%
c48
 
4.0%
.48
 
4.0%
g48
 
4.0%
Other values (23)515
43.4%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)100.0%
Missing80
Missing (%)93.0%
Infinite0
Infinite (%)0.0%
Mean390.5
Minimum30
Maximum755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2022-09-05T21:39:11.875082image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50.5
Q1177.5
median444
Q3547
95-th percentile705.75
Maximum755
Range725
Interquartile range (IQR)369.5

Descriptive statistics

Standard deviation277.1149581
Coefficient of variation (CV)0.709641378
Kurtosis-1.314693001
Mean390.5
Median Absolute Deviation (MAD)212.5
Skewness-0.1895491999
Sum2343
Variance76792.7
MonotonicityNot monotonic
2022-09-05T21:39:11.958418image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5141
 
1.2%
3741
 
1.2%
7551
 
1.2%
1121
 
1.2%
5581
 
1.2%
301
 
1.2%
(Missing)80
93.0%
ValueCountFrequency (%)
301
1.2%
1121
1.2%
3741
1.2%
5141
1.2%
5581
1.2%
7551
1.2%
ValueCountFrequency (%)
7551
1.2%
5581
1.2%
5141
1.2%
3741
1.2%
1121
1.2%
301
1.2%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing80
Missing (%)93.0%
Memory size816.0 B
ТВ-3
TV Globo
Show TV
RTL4
TV3

Length

Max length11
Median length7.5
Mean length6.166666667
Min length3

Characters and Unicode

Total characters37
Distinct characters24
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowТВ-3
2nd rowTV Globo
3rd rowShow TV
4th rowRTL4
5th rowTV3

Common Values

ValueCountFrequency (%)
ТВ-31
 
1.2%
TV Globo1
 
1.2%
Show TV1
 
1.2%
RTL41
 
1.2%
TV31
 
1.2%
USA Network1
 
1.2%
(Missing)80
93.0%

Length

2022-09-05T21:39:12.052369image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:12.152130image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
tv2
22.2%
тв-31
11.1%
globo1
11.1%
show1
11.1%
rtl41
11.1%
tv31
11.1%
usa1
11.1%
network1
11.1%

Most occurring characters

ValueCountFrequency (%)
T4
 
10.8%
o4
 
10.8%
V3
 
8.1%
3
 
8.1%
32
 
5.4%
S2
 
5.4%
w2
 
5.4%
Т1
 
2.7%
41
 
2.7%
r1
 
2.7%
Other values (14)14
37.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter17
45.9%
Lowercase Letter13
35.1%
Space Separator3
 
8.1%
Decimal Number3
 
8.1%
Dash Punctuation1
 
2.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T4
23.5%
V3
17.6%
S2
11.8%
Т1
 
5.9%
N1
 
5.9%
A1
 
5.9%
U1
 
5.9%
L1
 
5.9%
R1
 
5.9%
В1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
o4
30.8%
w2
15.4%
r1
 
7.7%
t1
 
7.7%
e1
 
7.7%
h1
 
7.7%
b1
 
7.7%
l1
 
7.7%
k1
 
7.7%
Decimal Number
ValueCountFrequency (%)
32
66.7%
41
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin28
75.7%
Common7
 
18.9%
Cyrillic2
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
T4
14.3%
o4
14.3%
V3
 
10.7%
S2
 
7.1%
w2
 
7.1%
r1
 
3.6%
t1
 
3.6%
e1
 
3.6%
N1
 
3.6%
A1
 
3.6%
Other values (8)8
28.6%
Common
ValueCountFrequency (%)
3
42.9%
32
28.6%
41
 
14.3%
-1
 
14.3%
Cyrillic
ValueCountFrequency (%)
Т1
50.0%
В1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII35
94.6%
Cyrillic2
 
5.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T4
 
11.4%
o4
 
11.4%
V3
 
8.6%
3
 
8.6%
32
 
5.7%
S2
 
5.7%
w2
 
5.7%
41
 
2.9%
r1
 
2.9%
t1
 
2.9%
Other values (12)12
34.3%
Cyrillic
ValueCountFrequency (%)
Т1
50.0%
В1
50.0%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing80
Missing (%)93.0%
Memory size816.0 B
Russian Federation
Brazil
Turkey
Netherlands
Sweden

Length

Max length18
Median length15.5
Mean length10
Min length6

Characters and Unicode

Total characters60
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowRussian Federation
2nd rowBrazil
3rd rowTurkey
4th rowNetherlands
5th rowSweden

Common Values

ValueCountFrequency (%)
Russian Federation1
 
1.2%
Brazil1
 
1.2%
Turkey1
 
1.2%
Netherlands1
 
1.2%
Sweden1
 
1.2%
United States1
 
1.2%
(Missing)80
93.0%

Length

2022-09-05T21:39:12.239565image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:12.333567image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
russian1
12.5%
federation1
12.5%
brazil1
12.5%
turkey1
12.5%
netherlands1
12.5%
sweden1
12.5%
united1
12.5%
states1
12.5%

Most occurring characters

ValueCountFrequency (%)
e9
15.0%
a5
 
8.3%
n5
 
8.3%
t5
 
8.3%
s4
 
6.7%
i4
 
6.7%
d4
 
6.7%
r4
 
6.7%
S2
 
3.3%
2
 
3.3%
Other values (14)16
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter50
83.3%
Uppercase Letter8
 
13.3%
Space Separator2
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e9
18.0%
a5
10.0%
n5
10.0%
t5
10.0%
s4
8.0%
i4
8.0%
d4
8.0%
r4
8.0%
l2
 
4.0%
u2
 
4.0%
Other values (6)6
12.0%
Uppercase Letter
ValueCountFrequency (%)
S2
25.0%
R1
12.5%
N1
12.5%
T1
12.5%
B1
12.5%
F1
12.5%
U1
12.5%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin58
96.7%
Common2
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e9
15.5%
a5
 
8.6%
n5
 
8.6%
t5
 
8.6%
s4
 
6.9%
i4
 
6.9%
d4
 
6.9%
r4
 
6.9%
S2
 
3.4%
l2
 
3.4%
Other values (13)14
24.1%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII60
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e9
15.0%
a5
 
8.3%
n5
 
8.3%
t5
 
8.3%
s4
 
6.7%
i4
 
6.7%
d4
 
6.7%
r4
 
6.7%
S2
 
3.3%
2
 
3.3%
Other values (14)16
26.7%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing80
Missing (%)93.0%
Memory size816.0 B
RU
BR
TR
NL
SE

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters12
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowRU
2nd rowBR
3rd rowTR
4th rowNL
5th rowSE

Common Values

ValueCountFrequency (%)
RU1
 
1.2%
BR1
 
1.2%
TR1
 
1.2%
NL1
 
1.2%
SE1
 
1.2%
US1
 
1.2%
(Missing)80
93.0%

Length

2022-09-05T21:39:12.413692image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:12.502990image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ru1
16.7%
br1
16.7%
tr1
16.7%
nl1
16.7%
se1
16.7%
us1
16.7%

Most occurring characters

ValueCountFrequency (%)
R3
25.0%
U2
16.7%
S2
16.7%
B1
 
8.3%
T1
 
8.3%
N1
 
8.3%
L1
 
8.3%
E1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter12
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R3
25.0%
U2
16.7%
S2
16.7%
B1
 
8.3%
T1
 
8.3%
N1
 
8.3%
L1
 
8.3%
E1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Latin12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R3
25.0%
U2
16.7%
S2
16.7%
B1
 
8.3%
T1
 
8.3%
N1
 
8.3%
L1
 
8.3%
E1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R3
25.0%
U2
16.7%
S2
16.7%
B1
 
8.3%
T1
 
8.3%
N1
 
8.3%
L1
 
8.3%
E1
 
8.3%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing80
Missing (%)93.0%
Memory size816.0 B
Asia/Kamchatka
America/Noronha
Europe/Istanbul
Europe/Amsterdam
Europe/Stockholm

Length

Max length16
Median length15.5
Mean length15.33333333
Min length14

Characters and Unicode

Total characters92
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowAsia/Kamchatka
2nd rowAmerica/Noronha
3rd rowEurope/Istanbul
4th rowEurope/Amsterdam
5th rowEurope/Stockholm

Common Values

ValueCountFrequency (%)
Asia/Kamchatka1
 
1.2%
America/Noronha1
 
1.2%
Europe/Istanbul1
 
1.2%
Europe/Amsterdam1
 
1.2%
Europe/Stockholm1
 
1.2%
America/New_York1
 
1.2%
(Missing)80
93.0%

Length

2022-09-05T21:39:12.590160image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:12.689041image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka1
16.7%
america/noronha1
16.7%
europe/istanbul1
16.7%
europe/amsterdam1
16.7%
europe/stockholm1
16.7%
america/new_york1
16.7%

Most occurring characters

ValueCountFrequency (%)
a9
 
9.8%
r8
 
8.7%
o8
 
8.7%
e7
 
7.6%
/6
 
6.5%
m6
 
6.5%
A4
 
4.3%
c4
 
4.3%
u4
 
4.3%
t4
 
4.3%
Other values (17)32
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter72
78.3%
Uppercase Letter13
 
14.1%
Other Punctuation6
 
6.5%
Connector Punctuation1
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a9
12.5%
r8
11.1%
o8
11.1%
e7
9.7%
m6
 
8.3%
c4
 
5.6%
u4
 
5.6%
t4
 
5.6%
p3
 
4.2%
s3
 
4.2%
Other values (8)16
22.2%
Uppercase Letter
ValueCountFrequency (%)
A4
30.8%
E3
23.1%
N2
15.4%
I1
 
7.7%
K1
 
7.7%
S1
 
7.7%
Y1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
/6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin85
92.4%
Common7
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a9
 
10.6%
r8
 
9.4%
o8
 
9.4%
e7
 
8.2%
m6
 
7.1%
A4
 
4.7%
c4
 
4.7%
u4
 
4.7%
t4
 
4.7%
p3
 
3.5%
Other values (15)28
32.9%
Common
ValueCountFrequency (%)
/6
85.7%
_1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a9
 
9.8%
r8
 
8.7%
o8
 
8.7%
e7
 
7.6%
/6
 
6.5%
m6
 
6.5%
A4
 
4.3%
c4
 
4.3%
u4
 
4.3%
t4
 
4.3%
Other values (17)32
34.8%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing86
Missing (%)100.0%
Memory size816.0 B

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing86
Missing (%)100.0%
Memory size816.0 B

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing86
Missing (%)100.0%
Memory size816.0 B

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing86
Missing (%)100.0%
Memory size816.0 B

Interactions

2022-09-05T21:39:02.331058image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:52.631387image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.570505image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.404126image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.269896image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.176399image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.079866image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.922132image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.768702image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.642591image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.540767image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.437816image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.400222image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:52.812392image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.635267image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.466046image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.341001image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.249958image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.145964image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.986992image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.842196image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.725016image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.621231image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.505992image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.465749image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:52.889219image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.706033image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.536424image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.419259image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.330135image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.218380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.068748image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.920487image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.800219image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.693123image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.579871image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.534165image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:52.957255image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.775004image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.609162image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.494447image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.406662image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.285333image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.140141image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.995185image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.875706image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.764039image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.649673image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.610098image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.024054image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.842863image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.682250image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.573972image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.497251image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.358133image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.211291image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.072384image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.947398image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.842274image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.722720image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.677639image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.094233image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.914006image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.755386image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.646033image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.574044image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.432970image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.284434image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.143435image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.015579image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.919235image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.793062image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.747571image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.160847image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.983187image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.828485image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.720998image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.650023image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.506403image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.352781image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.220237image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.090822image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.996895image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.867206image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.822502image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.227397image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.052591image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.908398image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.800106image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.733127image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.581993image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.422431image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.288899image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.174067image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.077016image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.957758image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.882311image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.289166image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.118793image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.975873image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.866308image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.804641image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.645707image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.489334image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.352204image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.242617image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.148417image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.027590image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.947706image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.358996image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.192180image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.046132image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.934360image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.872145image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.710444image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.555455image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.421933image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.314095image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.218759image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.097913image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:03.018544image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.433891image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.263908image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.124518image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.013253image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.943851image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.782116image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.623736image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.497290image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.392498image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.296924image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.185136image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:03.084506image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:53.503715image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:54.336054image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:55.198778image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:56.094913image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.012004image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:57.851719image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:58.696748image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:38:59.571736image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:00.465938image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:01.367661image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:02.261045image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:39:12.792235image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:39:13.055828image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:39:13.310694image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:39:13.611657image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:39:03.464754image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:39:04.166020image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:39:04.674715image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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32140386https://www.tvmaze.com/episodes/2140386/going-seventeen-2020-12-07-dont-lie-ii-2Don't Lie Ⅱ #2202041.0regular2020-12-072020-12-07T03:00:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/214038656655https://www.tvmaze.com/shows/56655/going-seventeenGoing SeventeenVarietyKorean[]Running30.030.02017-06-12NoneNone08:00[Wednesday]NaN69NaN122.0V LIVEKorea, Republic ofKRAsia/Seoulhttps://www.vlive.tv/homeNoneNaN330462.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/394/985825.jpghttps://static.tvmaze.com/uploads/images/original_untouched/394/985825.jpg<p>Initially a series of behind-the-scenes vlogs, <b>Going Seventeen</b> has taken a more structured route since mid-2019 and is now a reality-variety show with themed episodes. Every week, the members of Seventeen play games or participate in a variety of activities for everyone's delight and entertainment. Season 2021's keyword is "Watch What You Say", meaning that anything the members say can and will be turned into content...</p>1662048054https://api.tvmaze.com/shows/56655https://api.tvmaze.com/episodes/2383576https://api.tvmaze.com/episodes/2383577NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
41945591https://www.tvmaze.com/episodes/1945591/my-little-invisible-being-1x11-episode-11Episode 11111.0regular2020-12-0712:002020-12-07T04:00:00+00:005.0NaNNoneNaNhttps://api.tvmaze.com/episodes/194559150916https://www.tvmaze.com/shows/50916/my-little-invisible-beingMy Little Invisible BeingAnimationChinese[Comedy, Anime]Running5.05.02020-10-05Nonehttps://www.bilibili.com/bangumi/media/md28229943/12:00[Monday]NaN4NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/276/690795.jpghttps://static.tvmaze.com/uploads/images/original_untouched/276/690795.jpg<p>One day in 20XX, the alien pig prince who planned to take a human body as his home arrived on Earth, but unexpectedly discovered that the human being he wanted to live in had not yet been born! The pig prince, who has nowhere to settle down, got to know Saiji and Rubi. The three pulled various funny pranks on humans, causing humans to have baldness, bad breath, headaches, emotional crisis and other problems.</p>1602172227https://api.tvmaze.com/shows/50916https://api.tvmaze.com/episodes/1945592NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52065440https://www.tvmaze.com/episodes/2065440/the-wonderland-of-ten-thousands-4x27-episode-27-155Episode 27 (155)427.0regular2020-12-072020-12-07T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/206544054610https://www.tvmaze.com/shows/54610/the-wonderland-of-ten-thousandsThe Wonderland of Ten ThousandsAnimationChinese[Anime, Fantasy, Romance]Running10.010.02018-03-30Nonehttps://v.qq.com/detail/5/5cuf8ahvxvm2587.html10:00[Monday, Thursday]NaN67NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NoneNaN347112.0tt12923874https://static.tvmaze.com/uploads/images/medium_portrait/304/762299.jpghttps://static.tvmaze.com/uploads/images/original_untouched/304/762299.jpg<p>The master of Ye Xing Yun will ascend to heaven, leaving behind the great strength of the Tian Yuan Sect, and Ye Xing Yun making the new Sovereign of the Tian Yuan Sect, and at the request of his master, seek revenge by entering into a small family while waiting to perform revenge. Ye Xing Yun embarks on an extremely dangerous road, but with his strategy, and with the help of the masters of the Tian Yuan Sect, his long-term strategy of confrontation with the huge Zhou dynasty.</p>1661632267https://api.tvmaze.com/shows/54610https://api.tvmaze.com/episodes/2381296https://api.tvmaze.com/episodes/2381297NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
62080223https://www.tvmaze.com/episodes/2080223/supreme-god-emperor-1x61-episode-61Episode 61161.0regular2020-12-072020-12-07T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/208022355019https://www.tvmaze.com/shows/55019/supreme-god-emperorSupreme God EmperorAnimationChinese[Anime]Running10.010.02020-05-18Nonehttps://v.qq.com/detail/m/mzc00200ilydv1a.html10:00[Monday, Friday]NaN60NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NoneNaN388383.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/311/778540.jpghttps://static.tvmaze.com/uploads/images/original_untouched/311/778540.jpg<p>Ten thousand years ago, Muyun's fairy King was secretly accounted for by holding a Zhuxian figure, and after a long sleep, he awakened in the famous "Muyun waste" of the southern Yun Empire in the Land of Heaven. When Muyun first woke up, he was deliberately bothered by the student Miaoxianyu. Muyun easily completed the Miaoxianyu trap, and he gave more and more alchemy skills by analogy, so the Alchemy masters outside the door could not ask for appreciation. Endless back home, Mu Yun learns that he is about to marry Nona Qin Qin Mengyao. Qin Mengyao was cold and toxic, but could not live until he was 20 years old. The marriage was only for the sake of pastoralists and family of Qin. However, under Mu Linchen's enticement, Mu Yun approves the family's issue on the condition of alchemy.</p><p><br /> </p>1653896222https://api.tvmaze.com/shows/55019https://api.tvmaze.com/episodes/2257583NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71977315https://www.tvmaze.com/episodes/1977315/stjernestov-1x07-episode-7Episode 717.0regular2020-12-0706:002020-12-07T05:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197731550752https://www.tvmaze.com/shows/50752/stjernestovStjernestøvScriptedNorwegian[Drama, Children, Family]Ended20.020.02020-12-012020-12-24https://tv.nrk.no/serie/stjernestoev06:00[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN20NaN238.0NRK TVNorwayNOEurope/OsloNoneNoneNaN392649.0tt11492320https://static.tvmaze.com/uploads/images/medium_portrait/288/721951.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/721951.jpg<p>The parents get divorced and Jo has to move to a new place. One day, Nordstjerna goes out, and Jo discovers that a girl with magical powers lives in the attic.</p>1611436842https://api.tvmaze.com/shows/50752https://api.tvmaze.com/episodes/1977332NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726341.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726341.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaN
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Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.href_embedded.show._links.nextepisode.hrefimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel.country_embedded.show.image_embedded.show.webChannel
761977576https://www.tvmaze.com/episodes/1977576/atop-the-fourth-wall-12x45-awesome-comics-holiday-special-1Awesome Comics Holiday Special #11245.0regular2020-12-072020-12-07T17:00:00+00:0025.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197757618971https://www.tvmaze.com/shows/18971/atop-the-fourth-wallAtop the Fourth WallVarietyEnglish[]Running25.025.02008-10-26Nonehttp://www.atopthefourthwall.com[Monday]NaN29NaN40.0BlipUnited StatesUSAmerica/New_YorkNoneNoneNaN247956.0tt1868207https://static.tvmaze.com/uploads/images/medium_portrait/65/164161.jpghttps://static.tvmaze.com/uploads/images/original_untouched/65/164161.jpg<p><b>Atop the Fourth Wall</b> is a comic book review show, hosted by Lewis "Linkara" Lovhaug. The show specializes in reviewing really bad comic books.</p>1660915710https://api.tvmaze.com/shows/18971https://api.tvmaze.com/episodes/2330184https://api.tvmaze.com/episodes/2330185NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
772036537https://www.tvmaze.com/episodes/2036537/raw-talk-4x28-raw-talk-38Raw Talk 38428.0regular2020-12-072020-12-07T17:00:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/203653722473https://www.tvmaze.com/shows/22473/raw-talkRAW TalkTalk ShowEnglish[Sports]Running30.030.02016-10-30Nonehttps://watch.wwe.com/in-ring/Raw-Talk-1004[Monday]NaN28NaN15.0WWE NetworkUnited StatesUSAmerica/New_YorkNoneNoneNaN335558.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/409/1024249.jpghttps://static.tvmaze.com/uploads/images/original_untouched/409/1024249.jpg<p>On <b>RAW Talk</b>, Renee Young catches up with your favorite WWE RAW Superstars after each episode of "RAW" airs on the USA Network to hear their thoughts on all of that evening's action.</p>1660234141https://api.tvmaze.com/shows/22473https://api.tvmaze.com/episodes/2350915https://api.tvmaze.com/episodes/2350916NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
782014192https://www.tvmaze.com/episodes/2014192/true-colors-1x04-alex-rodriguezAlex Rodriguez14.0regular2020-12-072020-12-07T17:00:00+00:0012.0NaN<p>From humble beginnings to legendary baseball player and current CEO, A-Rod shares his success story.</p>NaNhttps://api.tvmaze.com/episodes/201419250918https://www.tvmaze.com/shows/50918/true-colorsTrue ColorsDocumentaryEnglish[]To Be DeterminedNaN16.02020-09-29Nonehttps://www.peacocktv.com/truecolors[Tuesday]NaN64NaN347.0PeacockUnited StatesUSAmerica/New_Yorkhttps://www.peacocktv.com/NoneNaNNaNtt13135554https://static.tvmaze.com/uploads/images/medium_portrait/276/690841.jpghttps://static.tvmaze.com/uploads/images/original_untouched/276/690841.jpg<p>An intimate and vivid portrait of the stories of successful Hispanics living in the United States. Enlightening audiences and showing their True Colors through a closer look at their beginnings, struggles, family, and close friends.</p>1630797391https://api.tvmaze.com/shows/50918https://api.tvmaze.com/episodes/2014196NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/293/734732.jpghttps://static.tvmaze.com/uploads/images/original_untouched/293/734732.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaN
791960031https://www.tvmaze.com/episodes/1960031/goede-tijden-slechte-tijden-31x57-aflevering-6312Aflevering 63123157.0regular2020-12-0720:002020-12-07T19:00:00+00:0023.0NaNNoneNaNhttps://api.tvmaze.com/episodes/19600312504https://www.tvmaze.com/shows/2504/goede-tijden-slechte-tijdenGoede Tijden, Slechte TijdenScriptedDutch[Drama, Romance]Running23.025.01990-10-01Nonehttp://gtst.nl/#!/20:00[Monday, Tuesday, Wednesday, Thursday]NaN83NaNNaNNaNNaNNaNNaNNaNNone19056.0104271.0tt0096597https://static.tvmaze.com/uploads/images/medium_portrait/332/830481.jpghttps://static.tvmaze.com/uploads/images/original_untouched/332/830481.jpgNone1662346277https://api.tvmaze.com/shows/2504https://api.tvmaze.com/episodes/2379702https://api.tvmaze.com/episodes/2379703https://static.tvmaze.com/uploads/images/medium_landscape/286/716332.jpghttps://static.tvmaze.com/uploads/images/original_untouched/286/716332.jpg112.0RTL4NetherlandsNLEurope/AmsterdamNaNNaNNaNNaN
801986262https://www.tvmaze.com/episodes/1986262/frusna-vagar-6x07-episode-7Episode 767.0regular2020-12-0720:002020-12-07T19:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198626235597https://www.tvmaze.com/shows/35597/frusna-vagarFrusna vägarRealitySwedish[]Running60.060.02018-01-30Nonehttps://www.viafree.se/program/reality/frusna-vagar20:00[Tuesday]NaN30NaN191.0ViafreeNaNNaNNaNNoneNoneNaN341150.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/150/376405.jpghttps://static.tvmaze.com/uploads/images/original_untouched/150/376405.jpg<p>Join a sparkling Sweden far up in the north where snow and ice are everyday for both bearers and snowmen, but not as comfortable for big city residents on a temporary visit. In Frozen roads, we go out on the roads along with the heroes who turn the northern borders into dangerous areas, despite Kung Boro's hard resistance. When the wind suddenly sweeps into the sparkling fields in snowy wrecking, the roads shine glashala and the drifting snow forms piles, then they have never longed so much for the heroes of the winter roads.</p>1644329789https://api.tvmaze.com/shows/35597https://api.tvmaze.com/episodes/2272638NaNNaNNaN558.0TV3SwedenSEEurope/StockholmNaNNaNNaNNaN
811978062https://www.tvmaze.com/episodes/1978062/prince-charming-2x09-folge-9Folge 929.0regular2020-12-0720:152020-12-07T19:15:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197806245015https://www.tvmaze.com/shows/45015/prince-charmingPrince CharmingRealityGerman[Romance]Running60.060.02019-10-30Nonehttps://www.tvnow.de/shows/prince-charming-1774220:15[Tuesday]NaN48NaN368.0RTL+GermanyDEEurope/BusingenNoneNoneNaN371505.0tt11219164https://static.tvmaze.com/uploads/images/medium_portrait/223/558964.jpghttps://static.tvmaze.com/uploads/images/original_untouched/223/558964.jpg<p>German version of a handsome man trying to find true love amongst a group of "princes". Who shall provide the happy ending?</p>1652913157https://api.tvmaze.com/shows/45015https://api.tvmaze.com/episodes/2182395NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
821981614https://www.tvmaze.com/episodes/1981614/inside-poundland-secrets-from-the-shop-floor-1x01-episode-1Episode 111.0regular2020-12-0721:002020-12-07T21:00:00+00:0060.0NaN<p>Managing director Barry visits the Walsall branch to help with the launch of Project Diamond - a multimillion-pound investment into giving stores a makeover and branching into new product lines like frozen and chilled food.</p>NaNhttps://api.tvmaze.com/episodes/198161452287https://www.tvmaze.com/shows/52287/inside-poundland-secrets-from-the-shop-floorInside Poundland: Secrets from the Shop FloorDocumentaryEnglish[]To Be Determined60.060.02020-12-07Nonehttps://www.channel4.com/programmes/inside-poundland-secrets-from-the-shop-floor21:00[Monday]NaN34NaN52.0All 4United KingdomGBEurope/Londonhttps://www.channel4.com/NoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/718116.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/718116.jpg<p>From bargain to deluxe, Poundland are on a mission to transform their reputation and go upmarket, from investing millions on opening new stores and undergoing refits to launching new product ranges.</p>1607382073https://api.tvmaze.com/shows/52287https://api.tvmaze.com/episodes/1981615NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
831981615https://www.tvmaze.com/episodes/1981615/inside-poundland-secrets-from-the-shop-floor-1x02-episode-2Episode 212.0regular2020-12-0721:002020-12-07T21:00:00+00:0060.0NaN<p>Area manager Colin prepares for the opening day of a new store in Stockton-on-Tees, while managing director Barry oversees the national launch of a homeware range.</p>NaNhttps://api.tvmaze.com/episodes/198161552287https://www.tvmaze.com/shows/52287/inside-poundland-secrets-from-the-shop-floorInside Poundland: Secrets from the Shop FloorDocumentaryEnglish[]To Be Determined60.060.02020-12-07Nonehttps://www.channel4.com/programmes/inside-poundland-secrets-from-the-shop-floor21:00[Monday]NaN34NaN52.0All 4United KingdomGBEurope/Londonhttps://www.channel4.com/NoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/718116.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/718116.jpg<p>From bargain to deluxe, Poundland are on a mission to transform their reputation and go upmarket, from investing millions on opening new stores and undergoing refits to launching new product ranges.</p>1607382073https://api.tvmaze.com/shows/52287https://api.tvmaze.com/episodes/1981615NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
841972711https://www.tvmaze.com/episodes/1972711/wwe-monday-night-raw-27x49-1437-amway-center-in-orlando-fl#1437 - Amway Center in Orlando, FL2749.0regular2020-12-0720:002020-12-08T01:00:00+00:00180.0NaNNone6.0https://api.tvmaze.com/episodes/1972711802https://www.tvmaze.com/shows/802/wwe-monday-night-rawWWE Monday Night RAWSportsEnglish[]Running180.0181.01993-01-11Nonehttp://www.wwe.com/20:00[Monday]7.595NaN15.0WWE NetworkUnited StatesUSAmerica/New_YorkNoneNone6659.076779.0tt0185103https://static.tvmaze.com/uploads/images/medium_portrait/357/892591.jpghttps://static.tvmaze.com/uploads/images/original_untouched/357/892591.jpg<p><b>WWE Monday Night RAW</b> is World Wrestling Entertainment's (formerly the WWF and the WWWF before that) premiere wrestling event and brand. Since its launch in 1993, WWE Monday Night RAW continues to air live on Monday nights. It is generally seen as the company's flagship program due to its prolific history, high ratings, weekly live format, and emphasis on pay-per-views. Monday Night RAW is high profile enough to attract frequent visits from celebrities who usually serve as guest hosts for a single live event. Since its first episode, the show has been broadcast live or recorded from more than 197 different arenas in 165 cities and towns in seven different nations: including the United States, Canada, the United Kingdom twice a year, Afghanistan for a special Tribute to the Troops, Germany, Japan, Italy and Mexico.</p>1659846022https://api.tvmaze.com/shows/802https://api.tvmaze.com/episodes/2348842https://api.tvmaze.com/episodes/2348843NaNNaN30.0USA NetworkUnited StatesUSAmerica/New_YorkNaNNaNNaNNaN
852152584https://www.tvmaze.com/episodes/2152584/gang-wars-princes-1x09-serija-9Serija 919.0regular2020-12-0721:002020-12-08T02:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/215258457009https://www.tvmaze.com/shows/57009/gang-wars-princesGang Wars. PrincesScriptedLithuanian[Drama, Crime, Thriller]EndedNaN45.02020-10-122020-12-28https://go3.lt/series/gauju-karai-princai,serial-2042036[Monday]NaN16NaN518.0Go3NaNNaNNaNNoneNoneNaN401790.0tt13229878https://static.tvmaze.com/uploads/images/medium_portrait/350/876606.jpghttps://static.tvmaze.com/uploads/images/original_untouched/350/876606.jpg<p>Based on true events, the new Go3 original series is a crime story that may have taken place in the late 20th century in Lithuania. The story about one of the criminal groups "Princes" shows their methods of action, lifestyle and relationships with other criminal gangs.</p>1636217065https://api.tvmaze.com/shows/57009https://api.tvmaze.com/episodes/2152587NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN